Route Aware Predictive Congestion Control Protocol for Wireless Sensor Networks

Congestion in wireless sensor networks (WSN) may lead to packet losses or delayed delivery of important information rendering the WSN-based monitoring or control system useless. In this paper a routing-aware predictive congestion control (RPCC) yet decentralized scheme for WSN is presented that uses a combination of a hop by hop congestion control mechanism to maintain desired level of buffer occupancy, and a dynamic routing scheme that works in concert with the congestion control mechanism to forward the packets through less congested nodes. The proposed adaptive approach restricts the incoming traffic thus preventing buffer overflow while maintaining the rate through an adaptive back-off interval selection scheme. In addition, the optimal routing scheme diverts traffic from congested nodes through alternative paths in order to balance the load in the network, alleviating congestion. This load balancing of the routes will even out the congestion level throughout the network thus increasing throughput and reducing end to end delay. Closed-loop stability of the proposed hop-by-hop congestion control is demonstrated by using the Lyapunov-based approach. Simulation results show that the proposed scheme results in reduced end-to-end delays

Predictive Congestion Control Protocol for Wireless Sensor Networks

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks, result in a large number of packet drops, unfair scenarios and low throughputs with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, this paper presents a novel, decentralized, predictive congestion control (DPCC) for wireless sensor networks (WSN). The DPCC consists of an adaptive flow and adaptive back-off interval selection schemes that work in concert with energy efficient, distributed power control (DPC). The DPCC detects the onset of congestion using queue utilization and the embedded channel estimator algorithm in DPC that predicts the channel quality. Then, an adaptive flow control scheme selects suitable rate which is enforced by the newly proposed adaptive backoff interval selection scheme. An optional adaptive scheduling scheme updates weights associated with each packet to guarantee the weighted fairness during congestion. Closed-loop stability of the proposed hop-by-hop congestion control is demonstrated by using the Lyapunov-based approach. Simulation results show that the DPCC reduces congestion and improves performance over congestion detection and avoidance (CODA) [3] and IEEE 802.11 protocols

Smart data packet ad hoc routing protocol

This paper introduces a smart data packet routing protocol (SMART) based on swarm technology for mobile ad hoc networks. The main challenge facing a routing protocol is to cope with the dynamic environment of mobile ad hoc networks. The problem of finding best route between communication end points in such networks is an NP problem. Swarm algorithm is one of the methods used solve such a problem. However, copping with the dynamic environment will demand the use of a lot of training iterations. We present a new infrastructure where data packets are smart enough to guide themselves through best available route in the network. This approach uses distributed swarm learning approach which will minimize convergence time by using smart data packets. This will decrease the number of control packets in the network as well as it provides continues learning which in turn provides better reaction to changes in the network environment. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive packets in order to maintain and find better routes. This protocol is a hybrid Ant Colony Optimization (ACO) and river formation dynamics (RFD) swarm algorithms protocol. ACO is used to set up multi-path routes to destination at the initialization, while RFD mainly used as a base algorithm for the routing protocol. RFD offers many advantages toward implementing this approach. The main two reasons of using RFD are the small amount of information that required to be added to the packets (12 bytes in our approach) and the main idea of the RFD algorithm which is based on one kind of agent called drop that moves from source to destination only. This will eliminate the need of feedback packets to update the network and offers a suitable solution to change data packet into smart packets. Simulation results shows improvement in the throughput and reduction in end to end delay and jitter compared to AODV and AntHocNet protocols. © 2013 Elsevier B.V. All rights reserved

Performance Prediction and Tuning for Symmetric Coexistence of WiFi and ZigBee Networks

Due to the explosive deployment of WiFi and ZigBee wireless networks, 2.4GHz ISM bands (2.4GHz-2.5GHz) are becoming increasingly crowded, and the co-channel coexistence of these two networks is inevitable. For coexistence networks, people always want to predict their performance (e.g. throughput, energy consumption, etc.) before deployment, or even want to tune parameters to compensate unnecessary performance degradation (owing to the huge differences between these two MAC protocols) or to satisfy some performance requirements (e.g., priority, delay constraint, etc.) of them. However, predicting and tuning performance of coexisting WiFi and ZigBee networks has been a challenging task, primarily due to the lack of corresponding simulators and analytical models. In this dissertation, we addressed the aforementioned problems by presenting simulators and models for the coexistence of WiFi and ZigBee devices. Specifically, based on the energy efficiency and traffic pattern of three practical coexistence scenarios: disaster rescue site, smart hospital and home automation. We first of all classify them into three classes, which are non-sleeping devices with saturated traffic (SAT), non-sleeping devices with unsaturated traffic (UNSAT) and duty-cycling devices with unsaturated traffic (DC-UNSAT). Then a simulator and an analytical model are proposed for each class, where each simulator is verified by simple hardware based experiment. Next, we derive the expressions for performance metrics like throughput, delay etc., and predict them using both the proposed simulator and the model. Due to the higher accuracy of the simulator, the results from them are used as the ground truth to validate the accuracy of the model. Last, according to some common performance tuning requirements for each class, we formulate them into optimization problems and propose the corresponding solving methods. The results show that the proposed simulators have high accuracy in performance prediction, while the models, although are less accurate than the former, can be used in fast prediction. In particular, the models can also be easily used in optimization problems for performance tuning, and the results prove its high efficiency

Caracterização de redes sem fios multihop não planeadas

Mestrado em Engenharia de Computadores e TelemáticaA presente dissertação propõe-se realizar o mapeamento dos pontos de acesso 802.11 existentes da cidade de Aveiro. Recorrendo ao GPS obteve-se a localização de cada ponto. Com este mapeamento foi possível introduzir estes dados num ambiente de simulação para, posteriormente, com os dados obtidos na simulação, proceder-se a uma análise em detalhe dos dados obtidos e assim caracterizar a topologia da rede mapeada. Finalmente com todos os dados recolhidos, foram tiradas conclusões gerais sobre o estudo. Para este estudo contribuiu, um trabalho também realizado sobre uma experiência prática onde a densidade de terminais num meio envolvente a uma dada rede sem fios é comparado com a largura de banda disponível nas redes sem fios que operam no mesmo meio em diversas situações. Para realizar todo este trabalho foram desenvolvidos scripts em Python e C++.This dissertation tries to map the 802.11 access points in Aveiro city. Using a GPS device, every access point location in the city was gathered. Using this mapping information, it was possible, using a simulated environment, to come up with detailed data regarding the mapped network toppology. Finally, using all the obtained information, some general conclusions about the study were made. Another experiment also contributed to this study, regarding a network with dense distribution of terminals, in which the available bandwidth is comparable with the one on the wireless networks operating in a variety of conditions. To enable this study, several Python and C++ scripts/applications were developed

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

Optimising routing and trustworthiness of ad hoc networks using swarm intelligence

This thesis was submitted for the degree of Doctor of Philsophy and awarded by Brunel UniversityThis thesis proposes different approaches to address routing and security of MANETs using swarm technology. The mobility and infrastructure-less of MANET as well as nodes misbehavior compose great challenges to routing and security protocols of such a network. The first approach addresses the problem of channel assignment in multichannel ad hoc networks with limited number of interfaces, where stable route are more preferred to be selected. The channel selection is based on link quality between the nodes. Geographical information is used with mapping algorithm in order to estimate and predict the links’ quality and routes life time, which is combined with Ant Colony Optimization (ACO) algorithm to find most stable route with high data rate. As a result, a better utilization of the channels is performed where the throughput increased up to 74% over ASAR protocol. A new smart data packet routing protocol is developed based on the River Formation Dynamics (RFD) algorithm. The RFD algorithm is a subset of swarm intelligence which mimics how rivers are created in nature. The protocol is a distributed swarm learning approach where data packets are smart enough to guide themselves through best available route in the network. The learning information is distributed throughout the nodes of the network. This information can be used and updated by successive data packets in order to maintain and find better routes. Data packets act like swarm agents (drops) where they carry their path information and update routing information without the need for backward agents. These data packets modify the routing information based on different network metrics. As a result, data packet can guide themselves through better routes. In the second approach, a hybrid ACO and RFD smart data packet routing protocol is developed where the protocol tries to find shortest path that is less congested to the destination. Simulation results show throughput improvement by 30% over AODV protocol and 13% over AntHocNet. Both delay and jitter have been improved more than 96% over AODV protocol. In order to overcome the problem of source routing introduced due to the use of the ACO algorithm, a solely RFD based distance vector protocol has been developed as a third approach. Moreover, the protocol separates reactive learned information from proactive learned information to add more reliability to data routing. To minimize the power consumption introduced due to the hybrid nature of the RFD routing protocol, a forth approach has been developed. This protocol tackles the problem of power consumption and adds packets delivery power minimization to the protocol based on RFD algorithm. Finally, a security model based on reputation and trust is added to the smart data packet protocol in order to detect misbehaving nodes. A trust system has been built based on the privilege offered by the RFD algorithm, where drops are always moving from higher altitude to lower one. Moreover, the distributed and undefined nature of the ad hoc network forces the nodes to obligate to cooperative behaviour in order not to be exposed. This system can easily and quickly detect misbehaving nodes according to altitude difference between active intermediate nodes