MULTI PATH (MPTCP) in NS3

MULTI PATH  (MPTCP) in NS3

Introduction

MultiPath TCP (MPTCP) is an effort towards enabling the simultaneous use of several IP-addresses/interfaces by a modification of TCP that presents a regular TCP interface to applications, while in fact spreading data across several subflows. Benefits of this include better resource utilization, better throughput and smoother reaction to failures

Advantages:

The redundancy offered by Multipath TCP enables inverse multiplexing of resources, and thus increases TCP throughput to the sum of all available link-level channels instead of using a single one as required by plain TCP. Multipath TCP is backwards compatible with plain TCP.

Multipath TCP is particularly useful in the context of wireless networks - using both Wi-Fi and a mobile network is a typical use case. In addition to the gains in throughput from inverse multiplexing, links may be added or dropped as the user moves in or out of coverage without disrupting the end-to-end TCP connection. The problem of link handover is thus solved by abstraction in the transport layer, without any special mechanisms at the network or link level. Handover functionality can then be implemented at the endpoints without requiring special functionality in the subnetworks - in accordance to the Internet's end-to-end principle.

Multipath TCP also brings performance benefits in datacenter environments. In contrast to Ethernet channel bonding using 802.3ad link aggregation, Multipath TCP can balance a single TCP connection across multiple interfaces.

Results:

MPTCP Concept :

 To a non-MPTCP-aware application, MPTCP will behave the same as normal TCP. Extended APIs could provide additional control to MPTCP-aware applications. An application begins by opening a TCP socket in the normal way. MPTCP signaling and operation are handled by the MPTCP implementation.

An MPTCP connection begins similarly to a regular TCP connection. This is illustrated in Figure 2 where an MPTCP connection is established between addresses A1 and B1 on Hosts A and B, respectively.

 If extra paths are available, additional TCP sessions (termed MPTCP "subflows") are created on these paths, and are combined with the existing session, which continues to appear as a single connection to the applications at both ends. The creation of the additional TCP session is illustrated between Address A2 on Host A and Address B1 on Host B.

 MPTCP identifies multiple paths by the presence of multiple addresses at hosts. Combinations of these multiple addresses equate to the additional paths. In the example, other potential paths that could be set up are A1<->B2 and A2<->B2. Although this additional session is shown as being initiated from A2, it could equally have been initiated from B1. o The discovery and setup of additional subflows will be achieved through a path management method; this document describes a mechanism by which a host can initiate new subflows by using its own additional addresses, or by signaling its available addresses to the other host.

 MPTCP adds connection-level sequence numbers to allow the reassembly of segments arriving on multiple subflows with differing network delays.

 Subflows are terminated as regular TCP connections, with a four- way FIN handshake. The MPTCP connection is terminated by a connection-level FIN.

Networking Projects in NS2/ NS3/Matlab and .net

Project guidance in ,

• LTE/4G Networks,
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• Protocol Implementation for Mobile Adhoc Network in NS2/NS3
• Protocol Implementation for Wireless Sensor Networks in NS2/NS3
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• Video Streaming in NS2/NS3
• OBS Networks in NS2
• Attacker Implementation (Packet Dropping, Blackhole Attack, DDOS Attack, Packet Modification Attack and Greyhole Attack)
• Wimax Network in NS2 and NS3
• VANET (Vehicular Adhoc Network in ns2 using SUMO/mobisim)

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A Power Control MAC Protocol for Ad Hoc Networks 

This paper presents a power control MAC protocol that al-lows nodes to vary transmit power level on a per-packet basis. Several researchers have proposed simple modi_cations of IEEE 802.11 to incorporate power control. The main idea of these power control schemes is to use di_erent power levels for RTS-CTS and DATA-ACK. Speci_cally, maximum transmit power is used for RTS-CTS, and the minimum required transmit power is used for DATA-ACK transmissions in order to save energy. However, we show that these schemes can degrade network throughput and can result in higher energy consumption than when using IEEE 802.11 without power control. We propose a power control protocol which does not degrade throughput and yields energy saving.

 Zone Based Multicast Routing Protocol for Mobile Ad-Hoc Network

A Mobile Ad-hoc network (MANET) is composed of mobile nodes without using infrastructure. There are several virtual architectures used in the protocol without need of maintaining state information for more robust and scalable membership management. In this paper, we propose a Robust and Scalable Geographic Multicast protocol (RSGM). Both the control messages and data packets are forwarded along efficient tree-like paths, but there is no need to explicitly create and actively maintain a tree structure. To avoid periodic flooding of the source information throughout the network, a well-organized source tracking mechanism is designed. We are analyzing the protocols RSGM, SPBM and ODMRP with the performance metrics such as packet delivery ratio, control overhead, average path length and average joining delay by varying moving speed, node density, group size and network ranges.

 
An Efficient Mechanism to Detect Wormhole Attacks in Wireless Ad-hoc Networks

 
Important applications of Wireless Ad Hoc Networks make them very attractive to attackers, therefore more research is required to guarantee the security for Wireless Ad Hoc Networks. In this paper, we proposed a transmission time based mechanism (TTM) to detect wormhole attacks – one of the most popular & serious attacks in Wireless Ad Hoc Networks. TTM detects wormhole attacks during route setup procedure by computing transmission time between every two successive nodes along the established path. Wormhole is identified base on the fact that transmission time between two fake neighbors created by wormhole is considerably higher than that between two real neighbors which are within radio range of each other. TTM has good performance, little overhead and no special hardware required. TTM is designed specifically for Ad Hoc On-Demand Vector Routing Protocol (AODV) but it can be extended to work with other routing protocols.

 

Pre-allocation of Unused Bandwidth Algorithm: A QoS Control Protocol for 802.16 Network

we propose a new allocation method in this paper.With it, the allocation work is partitioned into three rounds. In the first round, the slots are allocated sequentially based on the maximal sustained rate of each queue. In the second round, the left slots are allocated with the Weighted Round Robin. If there are slots left, the packets in all queues have been scheduled after this round. Then, the third round can be continued. For this round, a method for forecasting the arrival rate of the arriving packets in each queue is proposed. Then, the left slots are assigned according to the fore casted arrival rate of each queue. Comparing to the other protocols, those packets sent in this round can be delivered almost one frame earlier. This can decrease the average delay of the network and improve the performance for the WiMAX system.

Toward Fuzzy Traffic Adaptation Solution in Wireless Mesh Networks

​Wireless technologies are becoming an essential part of our daily life. These technologies are expected to provide a wide variety of real-time applications; hence, there is a vital need to provide quality-of-Service (QoS) support. One of the key mechanisms to supportQoSis traffic egulation. Thebasic idea behind traffic regulation is to measure the network state (e.g., load) in order to adapt the rate of carefully selected application flows. In this paper, we propose a novel model, called FuzzyWMN, which can be used to implement traffic adaptation in Wireless Mesh Networks (WMNs).The objective of FuzzyWMNis to compute the rate adaptation to apply to application flows according to the current network state; it relies on two parameters to meet this objective: (1) packet delays between sources and destinations; and (2) buffer ccupancy of network nodes. The proposed model combines the essential notions of both fuzzy logic theory and Petri nets; this enables FuzzyWMN to realize traffic adaptation in networks characterized by information uncertainty and imprecision due to the dynamic traffic behavior, channel interferences, etc. Extensive simulations show that FuzzyWMN achieves stable end-to-end delay and good throughput under different network conditions.

The Three-Tier Security Scheme in Wireless Sensor Networks with Mobile Sinks

​Mobile sinks (MSs) are vital in many wireless sensor network (WSN) applications for efficient data accumulation, localized sensor reprogramming, and for distinguishing and revoking compromised sensors. However, in sensor networks that make use of the existing key predistribution schemes for pairwise key establishment and authentication between sensor nodes and mobile sinks, the employment of mobile sinks for data collection elevates a new security challenge: in the basic probabilistic and q-composite key predistribution schemes, an attacker can easily obtain a large number of keys by capturing a small fraction of nodes, and hence, can gain control of the network by deploying a replicated mobile sink preloaded with some compromised keys. This article describes a three-tier general framework that permits the use of any pairwise key predistribution scheme as its basic component. The new framework requires two separate key pools, one for the mobile sink to access the network, and one for pairwise key establishment between the sensors. To further reduce the damages caused by stationary access node replication attacks, we have strengthened the authentication mechanism between the sensor and the stationary access node in the proposed framework. Through detailed analysis, we show that our security framework has a higher network resilience to a mobile sink replication attack as compared to the polynomial pool-based scheme.

A Study of Energy-Aware Traffic Grooming in Optical Networks: Static and Dynamic Cases

Less attention has been given to energy aware optical counterparts, compared to the research in energy-aware wireless and ethernet networks. In this paper, we consider energy aware traffic grooming problems in optical networks for both static and dynamic cases. Rather than simply considering a logical architecture of an optical node, we specifically look further into the modular physical architecture. We show that by reusing already active physical components during request allocations, we can significantly reduce the total number of active components and, hence, total energy consumption in the network, especially when traffic load is low. Since energy usage is an important element of operational expenditure, this approach provides the financial motivation for service providers along with the desired environmental motivation. We present a mathematical formulation of the problems, propose auxiliary graph based heuristics,and justify our cases compared to traditional approaches, based on simulation results. Index Terms—Energy-efficiency, modular switch architecture,
optical networks, traffic grooming.

​​State-Aware Pointer Forwarding Scheme With Fast Handover Support in a PMIPv6 Domain

​Abstract—Proxy mobile IPv6 (PMIPv6) has been developed as a network-based mobility management protocol by the Internet Engineering Task Force. Mobility for individual mobile nodes (MNs) is supported by network entities. PMIPv6 thus eliminates mobility signaling from the MNs as it does not require a mobility stack at the MNs. However, during handovers of MNs, PMIPv6 induces unnecessary location update traffic and suffers the packet loss, which downgrades the quality of mobility support.In this paper, we introduce a state-aware pointer forwarding scheme with fast handover support, called FC-PMIPv6, to further enhance the performance of mobility support in a PMIPv6
domain. In FC-PMIPv6, a pointer forwarding chain between mobility access gateways (MAGs) is established to reduce location update traffic to a local mobility anchor during handovers of an MN. The current mobility state of the MN is also considered in deciding whether the forwarding chain should be prolonged or refreshed by an MAG serving the MN. This mobility state consideration in pointer forwarding reduces unnecessary traffic for the location update and guarantees the efficiency of packet transmission. In addition, a fast handover process is adopted to reduce the handover latency and avoid the packet loss during handovers. We develop analytical models to study the performance of FC-PMIPv6, which consider both the signaling cost and the packet transmission cost. Numerical results not only demonstrate that FC-PMIPv6 outperforms the basic PMIPv6 protocol, but also present a relationship between an optimized length of a forwarding chain and a mobility state of an MN.From the conducted numerical results, for example, it is shown that the signaling cost of FC-PMIPv6 is enhanced up to 23% over the basic PMIPv6 protocol. In addition, simulation results on the weighted signaling cost are provided to demonstrate the  performance improvement of our FC-PMIPv6 compared with the basic PMIPv6 protocol. Index Terms—Fast handover, packet transmission cost, pointer forwarding, proxy mobile IPv6 (PMIPv6), signaling cost.

​
A QoS-Oriented Distributed Routing Protocol for Hybrid Wireless Networks

​As wireless communication gains popularity, significant research has been devoted to supporting real-time transmission with stringent Quality of Service (QoS) requirements for wireless applications. At the same time, a wireless hybrid network that integrates a mobile wireless ad hoc network (MANET) and a wireless infrastructure network has been proven to be a better alternative for the next generation wireless networks. By directly adopting resource reservation-based QoS routing for MANETs, hybrids networks inherit invalid reservation and race condition problems in MANETs. How to guarantee the QoS in hybrid networks remains an open problem. In this paper, we propose a QoS-Oriented Distributed routing protocol (QOD) to enhance the QoS support capability of hybrid networks. Taking advantage of fewer transmission hops and anycast transmission features of the hybrid networks, QOD transforms the packet routing problem to a resource scheduling problem. QOD incorporates five algorithms: 1) a QoS-guaranteed neighbor selection algorithm to meet the transmission delay requirement, 2) a distributed packet scheduling algorithm to further reduce transmission delay, 3) a mobility-based segment resizing algorithm that adaptively adjusts segment size according to node mobility in order to reduce transmission time, 4) a traffic redundant elimination algorithm to increase the transmission throughput, and 5) a data redundancy elimination-based transmission algorithm to eliminate the redundant data to further improve the transmission QoS. Analytical and simulation results based on the random way-point model and the real human mobility model show that QOD can provide high QoS performance in terms of overhead, transmission delay, mobility-resilience, and scalability.
 

FLAP: An Efficient WLAN Initial Access Authentication Protocol

​Nowadays, with the rapid increase of WLAN-enabled mobile devices and the more widespread use of WLAN, it is increasingly important to have a more efficient initial link setup mechanism, and there is a demand for a faster access authentication method faster than the current IEEE 802.11i. In this paper, through experiments we observe that the authentication delay of 802.11i is intolerable under some scenarios, and we point that the main reason resulting in such inefficiency is due to its design from the framework perspective which introduces too many messages. To overcome this drawback, we propose an efficient initial access authentication protocol, FLAP, which realizes the authentications and key distribution through two roundtrip messages. We formally prove that our scheme is more secure than the four-way handshake protocol. Our practical measurement result indicates that FLAP can improve the efficiency of EAP-TLS by 94.7 percent. Extensive simulations are conducted in different scenarios, and the results demonstrate that when a WLAN gets crowded the advantage of FLAP becomes more salient. Furthermore, a simple and practical method is presented to make FLAP compatible with 802.11i. Index Terms—Authentication, WLAN, 802.11i

​COFFEE: A Context-Free Protocol for Stimulating Data Forwarding in Wireless Ad Hoc Networks

​Reputation based and credit-exchange based approaches have been studied extensively to enforce cooperation among non-cooperative nodes in wireless ad hoc networks. Most of the existing solutions are fundamentally context-based ones, which need to accurately identify selfish behaviors, securely maintain the context, and appropriately punish the selfish nodes. These requirements are extremely difficult to satisfy if not impossible. From a completely new angle, this paper proposes a context-free protocol, COFFEE, to enforce cooperation among
selfish nodes, which has the ability to transmit a packet over the path successfully without the dependency on the information of other packets’ transmission. Considering that every node in the network is rational, during the packet forwarding stage, if the intermediate nodes can not clearly tell whether the packet is destined to them or not, they can not simply drop the packet. Thus, in our proposed COFFEE protocol, through introducing several techniques, for any packet received by any node, the node thinks the packet could be destined to it and forwards the packet to find out the answer. Detailed analysis and performance evaluation have been conducted to demonstrate the effectiveness of the proposed protocol.

 Prioritized Optimal Channel Allocation Schemes for Multi-Channel Vehicular Networks

The IEEE 1609.4 standard has been proposed to provide multi-channel operations in wireless access for vehicular environments (WAVE), where all channels are periodically synchronized into control and service intervals. Communication device in each vehicle will stay at the control channel for negotiation and contention during the control interval, and thereafter switch to one of the service channels for data transmission in the service interval. In this paper, based on the concept of cognitive radio (CR), the vehicles are categorized into primary providers (PPs) that intend to transmit safety-related messages and secondary providers (SPs) with non-safety information to be delivered. The prioritized optimal channel allocation (POCA) approaches are proposed to improve channel utilization of IEEE 1609.4 standard for multi-channel vehicular networks. Prioritized channel access is analyzed in the POCA schemes in order to increase the transmission opportunity of PPs. Moreover, depending on whether the CR network is distributed or centralized, the optimal channel-hopping sequence and optimal channel allocation is assigned for SPs based on dynamic programming and linear programming technique, respectively. These schemes are designed to consider optimal load balance between both channel availability and channel utilization within the throughput constraints of PPs. With the adoption of proposed POCA schemes, simulation results show that maximum throughput of SPs can be achieved with guaranteed quality-of-service requirement for PPs.

SWIMMING: Seamless and Efficient WiFi-Based Internet Access from Moving Vehicles

Demand for Internet access from moving vehicles has been rapidly growing. Meanwhile, the overloading issue of cellular networks is escalating due to mobile data explosion. Thus, WiFi networks are considered as a promising technology to offload cellular networks. However, there pose many challenging problems in highly dynamic vehicular environments for WiFi networks. For example, connections can be easily disrupted by frequent handoffs between access points (APs). A scheme, called SWIMMING, is proposed to support seamless and efficient WiFi-based Internet access for moving vehicles. In uplink, SWIMMING operates in a “group unicast” manner. All APs are configured with the same MAC and IP addresses, so that packets sent from a client can be received by multiple APs within its transmission range. Unlike broadcast or monitor mode, group unicast exploits the diversity of multiple APs, while keeping all the advantages of unicast. To avoid possible collisions of ACKs from different APs, the conventional ACK decoding mechanism is enhanced with an ACK detection function. In downlink, a packet destined for a client is first pushed to a group of APs through multicast. This AP group is maintained dynamically to follow the moving client. The packet is then fetched by the client. With the above innovative design, SWIMMING achieves seamless roaming with reliable link, high throughput, and low packet loss. Testbed implementation and experiments are conducted to validate the effectiveness of the ACK detection function. Extensive simulations are carried out to evaluate the  performance of SWIMMING. Experimental results show that SWIMMING outperforms existing schemes remarkably.​

Multicast Rendezvous in Fast-Varying DSA Networks

Establishing communications between devices in a dynamic spectrum access (DSA) system requires the communicating parties to “rendezvous” before transmitting data packets. Frequency hopping (FH) is an effective rendezvous method that does not rely on a predetermined control channel. Previous FH-based rendezvous designs mainly target unicast rendezvous, and do not intrinsically support multicast rendezvous, where a group of nodes need to rendezvous simultaneously. Furthermore, these designs do not account for fast primary user (PU) dynamics, leading to long time-to-rendezvous (TTR). In this paper, we exploit the uniform  [k]  -arbiter and Chinese Remainder Theorem quorum systems to develop three FH-based multicast rendezvous algorithms, which provide different tradeoffs between rendezvous efficiency (e.g., low TTR) and security (e.g., robustness to node compromise). Our rendezvous algorithms are tailored for asynchronous and spectrum-heterogeneous DSA systems. To account for fast PU dynamics, we develop an algorithm for adapting the proposed FH designs on the fly. This adaptation is done through efficient mechanisms for channel ordering and quorum selection. Our simulations validate the effectiveness of the proposed rendezvous algorithms, their PU detection accuracy, and their robustness to insider attacks.

LTE/SAE Model and its Implementation in NS 2

Abstract — Expectation and requirements for future wireless communication systems continue to grow and evolve.  Thus, 3GPP has considered LTE/SAE to ensure its competitiveness in the future. In LTE/SAE, one of the recurring problems is dimensioning and testing, while model is the effective way to solve this problem because model is easy to generate test scenarios and inexpensive in changing test configurations and running test cases through modeling and simulation. The objective of this paper is to introduce how to build an accurate enough LTE/SAE model in NS 2 so that other optimization features can be tested. The simulation model includes traffic model and network model which concentrates on the air interface and S1 interface. At last, testing result of one scenario is given to demonstrate how to use this model.

                         I.           Introduction

LTE/SAE is an attempt to step into wireless broadband taken by cellular providers and equipment vendors. LTE/SAE introduces evolved radio interface with major enhancement coming from the use of Orthogonal Frequency Division Multiplexing (OFDM) and multiple antenna techniques.[1]These technologies are already available on the market and employed in WiMAX as specified in IEEE 802.16 standard.[2]Along with the evolved radio interface, LTE/SAE specifies the evolution of network architecture. It is designed to be packet-based and contain less network elements which reduce protocol processing overhead, latency and network deployment costs.

This paper will study LTE/SAE model and its implementation in NS2, and this task is the further study of the earlier one [3].  This paper is organized in this way: firstly, the LTE/SAE overview and the simulation tool NS 2 are described; secondly, the network model and its configuration in NS 2 are introduced. Thirdly, the traffic model and its configuration are presented. At last, we give an example to demonstrate how to use the model to analyze the performance of LTE/SAE.

A.    LTE/SAE overview

LTE/SAE is an Evolved Packet System (EPS) which includes the Evolved Universal Terrestrial Radio Access Network (E-UTRAN) and the evolved Packet Core (EPC).

The E-UTRAN consists of eNBs, providing the E-UTRA user plane (PDCP/RLC/MAC/PHY) and control plane (RRC) protocol terminations towards the UE. The eNBs are interconnected with each other by means of the X2 interface. The eNBs are also connected by means of the S1 interface to the EPC (Evolved Packet Core), more specifically to the MME (Mobility Management Entity) by means of the S1-MME and to the Serving Gateway (S-GW) by means of the S1-U. The S1 interface supports a many-to-many relation between MMEs / Serving Gateways and eNBs. The E-UTRAN architecture is illustrated in Figure 1.[3]

Figure 1 E-UTRAN architecture

The protocol stack for the user-plane is shown in Figure 2, where PDCP, RLC and MAC sublayers (terminated in eNB on the network side) perform the functions listed for the user plane, e.g. header compression, ciphering, scheduling, ARQ and HARQ;

Figure 2 user-plane protocol stack

The protocol stack for the control-plane is shown in Figure 3, where:

-        PDCP sublayer (terminated in eNB on the network side) performs the ciphering and integrity protection functions;

-        RLC and MAC sublayers (terminated in eNB on the network side) perform the same functions as for the user plane;

-        RRC (terminated in eNB on the network side) performs the following functions:

-           Broadcast;

-           Paging;

-           RRC connection management;

-           RB control;

-           Mobility functions;

-           UE measurement reporting and control.

-           NAS control protocol (terminated in MME on the network side) performs among other things:

-           EPS bearer management;

-           Authentication;

-           ECM-IDLE mobility handling;

-           Paging origination in ECM-IDLE;

-           Security control.

Figure 3 control-plane protocol stack

The main component of the SAE architecture is the Evolved Packet Core (EPC), also known as SAE Core. The EPC will serve as equivalent of GPRS networks (via the Mobility Management Entity, Serving Gateway and PDN Gateway subcomponents). The subcomponents of the EPC are:

-          MME (Mobility Management Entity): The MME is the key control-node for the LTE access-network. It is responsible for idle mode UE (User Equipment) tracking and paging procedure including retransmissions. It is involved in the bearer activation/deactivation process and is also responsible for choosing the SGW for a UE at the initial attach and at time of intra-LTE handover involving Core Network (CN) node relocation. It is responsible for authenticating the user (by interacting with the HSS). The Non-Access Stratum (NAS) signaling terminates at the MME and it is also responsible for generation and allocation of temporary identities to UEs. It checks the authorization of the UE to camp on the service provider’s Public Land Mobile Network (PLMN) and enforces UE roaming restrictions. The MME is the termination point in the network for ciphering/integrity protection for NAS signaling and handles the security key management. Lawful interception of signaling is also supported by the MME. The MME also provides the control plane function for mobility between LTE and 2G/3G access networks with the S3 interface terminating at the MME from the SGSN. The MME also terminates the S6a interface towards the home HSS for roaming UEs.

-          S-GW (Serving Gateway): The S-GW routes and forwards user data packets, while also acting as the mobility anchor for the user plane during inter-eNB handovers and as the anchor for mobility between LTE and other 3GPP technologies (terminating S4 interface and relaying the traffic between 2G/3G systems and PDN-GW). For idle state UEs, the S-GW terminates the DL data path and triggers paging when DL data arrives for the UE. It manages and stores UE contexts, e.g. parameters of the IP bearer service, network internal routing information. It also performs replication of the user traffic in case of lawful interception.

-          PDN-GW (Packet Data Network Gateway): The PDN-GW provides connectivity to the UE to external packet data networks by being the point of exit and entry of traffic for the UE. A UE may have simultaneous connectivity with more than one PDN-GW for accessing multiple PDNs. The PDN-GW performs policy enforcement, packet filtering for each user, charging support, lawful Interception and packet screening. Another key role of the PDN-GW is to act as the anchor for mobility between 3GPP and non-3GPP technologies such as WiMAX and 3GPP2 (CDMA 1X and EvDO). [4] [5]

B.    NS 2 overview

NS 2 began as a variant of the REAL network simulator in 1989 and has evolved substantially over the past few years. In 1995 NS development was supported by DARPA through the VINT project at LBL, Xerox PARC, UCB, and USC/ISI. Currently NS development is support through DARPA with SAMAN and through NSF with CONSER, both in collaboration with other researchers including ACIRI. NS has always included substantial contributions from other researchers, including wireless code from the UCB Daedelus and CMU Monarch projects and Sun Microsystems.[6]

NS 2 is a discrete event simulator targeted at networking research. NS 2 provides substantial support for simulation of TCP, routing, and multicast protocols over wired and wireless (local and satellite) networks. In the NS 2 simulation, all the data in the network is available, thus the performance of the network can be easily analyzed. What’s more, NS 2 is free and open source code and suitable to build system level simulation, so we use it to simulate LTE/SAE.

             II.         Network model and configuration

In our model, some network configuration parameters can easily be changed with TCL (Tool Command Language), for example we can define any number of UE, bandwidth between the network elements and the use of the optimization features; others can not be changed so easily due to the limitation of the implemented model, such as eNB and aGW number. The LTE/SAE network model and configuration are described in detail in the following sections.

A.    Network model

In our simulated LTE/SAE network, the following network elements are included:

·         1 server (provide HTTP, FTP and signaling services).

·         1 aGW (provide HTTP cache, flow control).

·         1 eNB (provide flow control information).

·         Many UEs.

Figure 4 LTE/SAE network model

Flow control

One of the key targets for the evolution of the radio-interface and radio-access network architecture is 100Mbps peak data rate in downlink.[7] While compared to the lined data rate, the wireless data rate is still a bottleneck. This means if we do not do the flow control in aGW, packets will be buffered in eNB. While the buffer in eNB is limited, packets may be dropped. To reduce the harm to the performance of the TCP from packet loss, flow control is needed. In our model, DLAirQueue provides each flows information, such as buffer size and average data rate; DLS1Queue uses this information and current packet size to decide whether the packet is allowed to be sent to DLAirQueue. If the buffer of the flow or the cell where the flow locates is going to be overflow, the packet is blocked until both the flow’s buffer and cell’s buffer is not overflow.

Handover

Following defines the handover support within E-UTRAN: [8]

-          The intra E-UTRAN handover in RRC_CONNECTED state is UE assisted network controlled handover with handover preparation signaling in E-UTRAN.

-          In E-UTRAN RRC_IDLE state, cell reselections are performed and DRX (Discontinuous Reception) is supported.

In E-UTRAN RRC_CONNECTED state, network controlled UE assisted handovers are performed and various DRX/DTX (Discontinuous Transmission) cycles are supported:

- UE performs neighbor cell measurements based on measurement control and neighbor cell information from the network;

- Network signals reporting criteria for event-triggered and possibly periodical reporting.

In our current model, handover process is simplified that UE always stays in the same cell. The handover model will be improved in the later study.

B.    Network configuration

Figure 5 Queue classes

In the model, new queue classes, such as LTEQueue, ULAirQueue, DLAirQueue, ULS1Queue and DLS1Queue, are implemented to simulate the air interface and S1 interface. The queue class inheritance is showed in Figure 5. The common implementation, such as whether the optimization feature is used, is defined in the parent class LTEQueue; the interface and direction specific implementation is defined in other four new queue classes.

Classification

When one packet enters LTEQueue, the packet is classified to its corresponding sub-queue according to its classid. If the QoS feature is triggered, the packet of class 0, class 1 and class 2 enters DropTail sub-queue respectively; the packet belonging to class 3 enters REDQueue sub-queue; if the QoS feature is not triggered, all the packets enter the same DropTail sub-queue.

Scheduling

If the QoS feature is triggered, strict priority is used when there is one packet can be sent, i.e. the packet to be sent is always in the flowing order class 0, class 1, class 2 and class 3; if the QoS feature is not triggered, round-robin is used to send one packet.

                     III.        Traffic model and configuration

A.    Traffic model

 When defining the UMTS QoS classes, also referred to as traffic classes, the restrictions and limitations of the air interface have to be taken into account. It is not reasonable to define complex mechanisms as have been in fixed networks due to different error characteristics of the air interface. The QoS mechanisms provided in the cellular network have to be robust and capable of providing reasonable QoS resolution. [8]

There are four different QoS classes:

-        conversational class;

-        streaming class;

-        interactive class; and

-        background class.

The main distinguishing factor between these QoS classes is how delay sensitive the traffic is: Conversational class is meant for traffic which is very delay sensitive while Background class is the most delay insensitive traffic class.

Conversational and Streaming classes are mainly intended to be used to carry real-time traffic flows. The main divider between them is how delay sensitive the traffic is. Conversational real-time services, like video telephony, are the most delay sensitive applications and those data streams should be carried in Conversational class.

Interactive class and Background are mainly meant to be used by traditional Internet applications like WWW, Email, Telnet, FTP and News. Due to looser delay requirements, compare to conversational and streaming classes, both provide better error rate by means of channel coding and retransmission. The main difference between Interactive and Background class is that Interactive class is mainly used by interactive applications, e.g. interactive Email or interactive Web browsing, while Background class is meant for background traffic, e.g. background download of Emails or background file downloading. Responsiveness of the interactive applications is ensured by separating interactive and background applications. Traffic in the Interactive class has higher priority in scheduling than Background class traffic, so background applications use transmission resources only when interactive applications do not need them. This is very important in wireless environment where the bandwidth is low compared to fixed networks.

However, these are only typical examples of usage of the traffic classes. There is in particular no strict one-to-one mapping between classes of service (as defined in TS 22.105 [8]) and the traffic classes defined in this TS. For instance, a service interactive by nature can very well use the Conversational traffic class if the application or the user has tight requirements on delay.

B.    Traffic configuration

The QoS supporting in LTE/SAE is simulated. Table 1 illustrates the QoS classes and simulated traffic for LTE/SAE.

Table 1 Traffic classes in LTE/SAE

Traffic class	Conversational class	Streaming class	Interactive class	Background
Fundamental characteristics	- Preserve time relation (variation) between information entities of the stream - Conversational pattern stringent and low delay	- Preserve time relation (variation) between information entities of the stream - One way transport	- Request response pattern - Preserve payload content	- Destination is not expecting the data within a certain time - Preserve payload content
Example of the application	- voice over IP - video conferencing - telephony speech	- streaming video/audio	- Web browsing - Database retrieval - Server access	- background download of emails, database, measurement records
Simulation traffic	Session/RTP - Session/RTPAgent - Session/RTCPAgent	- CBR/UdpAgent	HTTP/TcpAgent - HTTP/Client - HTTP/Cache - HTTP/Server	- FTP/TcpAgent
Main configuration parameters	- AMR rate - multi-side call - RTP interval - RTP packet size	- CBR rate - CBR packet size - random noise in the interval	- average page size - average page age - average request interval	- configure the TCP parameters

                                          IV.        Testing rsult of the model

This section demonstrates how to use the model to do other optimization of LTE/SAE network:

1.        Configure the simulation time, routing protocol, used feature (such as QoS, flow control).

2.        Configure the network model’s parameter: such as the number of UEs, buffer size of each class.

3.        Configure the traffic model’s parameter: such as the packet size, data rate.

4.        Run the simulation with the test script.

5.        Analyze the test result according to the statistic file.

Evaluation of the network performance is mainly based on the following criteria (These values can be got directly from the statistics file):

·         throughput

·         average delay

·         packet lost percent

Here is the example of one scenario:

From above figures, we can see

                                          V.         Conclusion

In this paper, a LTE/SAE model and its implementation in NS 2 are presented. To get more exact model, some additional work needs to be done, such as handover model. We will study some optimization algorithms based on this model to improve the performance of the LTE/SAE network in the future.