Experimental Performance Evaluation and Frame Aggregation Enhancement in IEEE 802.11n WLANs

The IEEE 802.11n standard promises to extend today’s most popular WLAN standard by significantly increasing reach, reliability, and throughput. Ratified on September 2009, this standard defines many new physical and medium access control (MAC) layer enhancements. These enhancements aim to provide a data transmission rate of up to 600 Mbps. Since June 2007, 802.11n products are available on the enterprise market based on the draft 2.0. In this paper we investigate the effect of most of the proposed 802.11n MAC and physical layer features on the adhoc networks performance. We have performed several experiments in real conditions. The experimental results demonstrated the effectiveness of 802.11n enhancement. We have also examined the interoperability and fairness of 802.11n. The frame aggregation mechanism of 802.11n MAC layer can improve the efficiency of channel utilization by reducing the protocol overheads. We focused on the effect of frame aggregation on the support of voice and video applications in wireless networks. We also propose a new frame aggregation scheduler that considers specific QoS requirements for multimedia applications. We dynamically adjust the aggregated frame size based on frame's access category defined in 802.11e standard

Efficient quality of service‐aware packet chunking scheme for machine‐to‐machine cloud services

With the recent advances in machine-to-machine(M2M) communications, huge numbers of devices have become connected and massive amounts of traffic are exchanged. M2M applications typically generate small packets, which can profoundly affect the network performance. Namely, even if the packet arrival rate at the router is lower than the link bandwidth, bits per second(BPS), it can exceed the router forwarding capacity, which indicates the maximum number of forwarded packets per second(PPS). This will cause the decrease in the network throughput. Therefore, eliminating the PPS limitation by chunking small packets will enable M2M cloud services to spread further. This paper proposes new packet-chunking schemes aimed at meeting both application requirements and improving achievable router throughput. In our schemes, multiple buffers, each of which accommodates packets classified based on their delay requirement, are installed in parallel. Herein, we report on analysis of the theoretically performance of these schemes, which enabled us to derive some important features. We also propose a scheme whereby a single chunking buffer and parallel multiple buffers were arranged in tandem. Through our simulation and numerical results, we determined that these schemes provide excellent performance in reducing the number of outgoing packets from the router while meeting various delay requirements.The 2nd IEEE International Workshop on High-Performance Interconnection Networks in the Exascale and Big-Data Era (IEEE HPCA 2016),March 12, 2016, Barcelona, Spai

An Adaptive Packet Aggregation Algorithm (AAM) for Wireless Networks

Packet aggregation algorithms are used to improve the throughput performance by combining a number of packets into a single transmission unit in order to reduce the overhead associated with each transmission within a packet-based communications network. However, the throughput improvement is also accompanied by a delay increase. The biggest drawback of a significant number of the proposed packet aggregation algorithms is that they tend to only optimize a single metric, i.e. either to maximize throughput or to minimize delay. They do not permit an optimal trade-off between maximizing throughput and minimizing delay. Therefore, these algorithms cannot achieve the optimal network performance for mixed traffic loads containing a number of different types of applications which may have very different network performance requirements. In this thesis an adaptive packet aggregation algorithm called the Adaptive Aggregation Mechanism (AAM) is proposed which achieves an aggregation trade-off in terms of realizing the largest average throughput with the smallest average delay compared to a number of other popular aggregation algorithms under saturation conditions in wireless networks. The AAM algorithm is the first packet aggregation algorithm that employs an adaptive selection window mechanism where the selection window size is adaptively adjusted in order to respond to the varying nature of both the packet size and packet rate. This algorithm is essentially a feedback control system incorporating a hybrid selection strategy for selecting the packets. Simulation results demonstrate that the proposed algorithm can (a) achieve a large number of sub-packets per aggregate packet for a given delay and (b) significantly improve the performance in terms of the aggregation trade-off for different traffic loads. Furthermore, the AAM algorithm is a robust algorithm as it can significantly improve the performance in terms of the average throughput in error-prone wireless networks

Performance modelling of fairness in IEEE 802.11 wireless LAN protocols

PhD ThesisWireless communication has become a key technology in the modern world, allowing network services to be delivered in almost any environment, without the need for potentially expensive and invasive fixed cable solutions. However, the level of performance experienced by wireless devices varies tremendously on location and time. Understanding the factors which can cause variability of service is therefore of clear practical and theoretical interest. In this thesis we explore the performance of the IEEE 802.11 family of wireless protocols, which have become the de facto standard for Wireless Local Area Networks (WLANs). The specific performance issue which is investigated is the unfairness which can arise due to the spatial position of nodes in the network. In this work we characterise unfairness in terms of the difference in performance (e.g. throughput) experienced by different pairs of communicating nodes within a network. Models are presented using the Markovian process algebra PEPA which depict different scenarios with three of the main protocols, IEEE 802.11b, IEEE 802.11g and IEEE 802.11n. The analysis shows that performance is affected by the presence of other nodes (including in the well-known hidden node case), by the speed of data and the size of the frames being transmitted. The collection of models and analysis in this thesis collectively provides not only an insight into fairness in IEEE 802.11 networks, but it also represents a significant use case in modelling network protocols using PEPA. PEPA and other stochastic process algebra are extremely powerful tools for efficiently specifying models which might be very complex to study using conventional simulation approaches. Furthermore the tool support for PEPA facilitates the rapid solution of models to derive key metrics which enable the modeller to gain an understanding of the network behaviour across a wide range of operating conditions. From the results we can see that short frames promote a greater fairness due to the more frequent spaces between frames allowing other senders to transmit. An interesting consequence of these findings is the observation that varying frame length can play a role in addressing topological unfairness, which leads to the analysis of a novel model of IEEE 802.11g with variable frame lengths. While varying frame lengths might not always be practically possible, as frames need to be long enough for collisions to be detected, IEEE 802.11n supports a number of mechanisms for frame aggregation, where successive frames may be sent in series with little or no delay between them. We therefore present a novel model of IEEE 802.11n with frame aggregation to explore how this approach affects fairness and, potentially, can be used to address unfairness by allowing affected nodes to transmit longer frame bursts.Kurdistan Region Government of Iraq (KRG) sponso