Congestion Avoidance And Fairness In Wireless Sensor Networks

Sensor network congestion avoidance and control primarily aims to reduce packet drops while maintaining fair bandwidth allocation to existing network flows. The design of a congestion control algorithm suited for all types of applications in sensor networks is a challenging task due to the application-specific nature of these networks. With numerous sensors transmitting data simultaneously to one or more base stations (also called sinks), sensor nodes located near the base station will most likely experience congestion and packet loss. In this thesis, we propose a novel distributed congestion avoidance algorithm which calculates the ratio of the number of downstream and upstream nodes. This ratio value (named Characteristic ratio) is used to take a routing decision and incorporate load balancing while also serving as a pointer to the congestion state of the network. Available queue sizes of the downstream nodes are used to detect incipient congestion. Queue characteristics of candidate downstream nodes are used collectively to implement both congestion avoidance and fairness by adjusting the node\u27s forwarding rate and next hop destination. Such an approach helps to minimize packet drops, improve energy efficiency and load balancing. In cases of severe congestion, the source is signaled to reduce its sending rate and enable the network recovery process. This is essentially a transport layer algorithm and would work best with a multi-path routing protocol and almost any MAC layer standard. We present the design and implementation of the proposed protocol and compare it with the existing avoidance protocols like Global rate control and Lightweight buffering. Our simulation results show a higher packet delivery ratio with greater node buffer utilization for our protocol in comparison with the conventional mechanisms

Congestion and medium access control in 6LoWPAN WSN

In computer networks, congestion is a condition in which one or more egressinterfaces are offered more packets than are forwarded at any given instant [1]. In wireless sensor networks, congestion can cause a number of problems including packet loss, lower throughput and poor energy efficiency. These problems can potentially result in a reduced deployment lifetime and underperforming applications. Moreover, idle radio listening is a major source of energy consumption therefore low-power wireless devices must keep their radio transceivers off to maximise their battery lifetime. In order to minimise energy consumption and thus maximise the lifetime of wireless sensor networks, the research community has made significant efforts towards power saving medium access control protocols with Radio Duty Cycling. However, careful study of previous work reveals that radio duty cycle schemes are often neglected during the design and evaluation of congestion control algorithms. This thesis argues that the presence (or lack) of radio duty cycle can drastically influence the performance of congestion control mechanisms. To investigate if previous findings regarding congestion control are still applicable in IPv6 over low power wireless personal area and duty cycling networks; some of the most commonly used congestion detection algorithms are evaluated through simulations. The research aims to develop duty cycle aware congestion control schemes for IPv6 over low power wireless personal area networks. The proposed schemes must be able to maximise the networks goodput, while minimising packet loss, energy consumption and packet delay. Two congestion control schemes, namely DCCC6 (Duty Cycle-Aware Congestion Control for 6LoWPAN Networks) and CADC (Congestion Aware Duty Cycle MAC) are proposed to realise this claim. DCCC6 performs congestion detection based on a dynamic buffer. When congestion occurs, parent nodes will inform the nodes contributing to congestion and rates will be readjusted based on a new rate adaptation scheme aiming for local fairness. The child notification procedure is decided by DCCC6 and will be different when the network is duty cycling. When the network is duty cycling the child notification will be made through unicast frames. On the contrary broadcast frames will be used for congestion notification when the network is not duty cycling. Simulation and test-bed experiments have shown that DCCC6 achieved higher goodput and lower packet loss than previous works. Moreover, simulations show that DCCC6 maintained low energy consumption, with average delay times while it achieved a high degree of fairness. CADC, uses a new mechanism for duty cycle adaptation that reacts quickly to changing traffic loads and patterns. CADC is the first dynamic duty cycle pro- tocol implemented in Contiki Operating system (OS) as well as one of the first schemes designed based on the arbitrary traffic characteristics of IPv6 wireless sensor networks. Furthermore, CADC is designed as a stand alone medium access control scheme and thus it can easily be transfered to any wireless sensor network architecture. Additionally, CADC does not require any time synchronisation algorithms to operate at the nodes and does not use any additional packets for the exchange of information between the nodes (For example no overhead). In this research, 10000 simulation experiments and 700 test-bed experiments have been conducted for the evaluation of CADC. These experiments demonstrate that CADC can successfully adapt its cycle based on traffic patterns in every traffic scenario. Moreover, CADC consistently achieved the lowest energy consumption, very low packet delay times and packet loss, while its goodput performance was better than other dynamic duty cycle protocols and similar to the highest goodput observed among static duty cycle configurations

Localized algorithm for aggregate fairness in wireless sensor networks

For data-collection applications in sensor networks, it is important to ensure all data sources have equal (or weighted) access to net-work bandwidth so that the base stations receive a complete picture about the monitored area. We point out the fairness problem in the current design of sensor networks, which may cause extremely biased bandwidth allocations. It is a challenge to design a fully distributed fairness solution due to the lack of global knowledge about the distribution of data sources and their routing paths. This paper proposes a new aggregate fairness model and a localized al-gorithm (called AFA) that implements the model. AFA is designed to work with any routing protocol. In particular, it allows the pack-ets from a data source to follow an arbitrary set of forwarding paths to the base stations. This flexibility makes it considerably harder to allocate bandwidth fairly among different data sources. AFA solves the problem with only localized operations at the sensors. It is easy to implement, which is an attractive property for sensor networks. Moreover, the algorithm automatically adjusts a sensor’s forwarding rate to avoid packet drops due to downstream conges-tion, which helps improve energy efficiency. We perform extensive simulations, demonstrating that the proposed algorithm can effec-tively improve end-to-end fairness

Centralized Rate Allocation and Control in 802.11-based Wireless Mesh Networks

Wireless Mesh Networks (WMNs) built with commodity 802.11 radios are a cost-effective means of providing last mile broadband Internet access. Their multihop architecture allows for rapid deployment and organic growth of these networks. 802.11 radios are an important building block in WMNs. These low cost radios are readily available, and can be used globally in license-exempt frequency bands. However, the 802.11 Distributed Coordination Function (DCF) medium access mechanism does not scale well in large multihop networks. This produces suboptimal behavior in many transport protocols, including TCP, the dominant transport protocol in the Internet. In particular, cross-layer interaction between DCF and TCP results in flow level unfairness, including starvation, with backlogged traffic sources. Solutions found in the literature propose distributed source rate control algorithms to alleviate this problem. However, this requires MAC-layer or transport-layer changes on all mesh routers. This is often infeasible in practical deployments. In wireline networks, router-assisted rate control techniques have been proposed for use alongside end-to-end mechanisms. We evaluate the feasibility of establishing similar centralized control via gateway mesh routers in WMNs. We find that commonly used router-assisted flow control schemes designed for wired networks fail in WMNs. This is because they assume that: (1) links can be scheduled independently, and (2) router queue buildups are sufficient for detecting congestion. These abstractions do not hold in a wireless network, rendering wired scheduling algorithms such as Fair Queueing (and its variants) and Active Queue Management (AQM) techniques ineffective as a gateway-enforceable solution in a WMN. We show that only non-work-conserving rate-based scheduling can effectively enforce rate allocation via a single centralized traffic-aggregation point. In this context we propose, design, and evaluate a framework of centralized, measurement-based, feedback-driven mechanisms that can enforce a rate allocation policy objective for adaptive traffic streams in a WMN. In this dissertation we focus on fair rate allocation requirements. Our approach does not require any changes to individual mesh routers. Further, it uses existing data traffic as capacity probes, thus incurring a zero control traffic overhead. We propose two mechanisms based on this approach: aggregate rate control (ARC) and per-flow rate control (PFRC). ARC limits the aggregate capacity of a network to the sum of fair rates for a given set of flows. We show that the resulting rate allocation achieved by DCF is approximately max-min fair. PFRC allows us to exercise finer-grained control over the rate allocation process. We show how it can be used to achieve weighted flow rate fairness. We evaluate the performance of these mechanisms using simulations as well as implementation on a multihop wireless testbed. Our comparative analysis show that our mechanisms improve fairness indices by a factor of 2 to 3 when compared with networks without any rate limiting, and are approximately equivalent to results achieved with distributed source rate limiting mechanisms that require software modifications on all mesh routers

Localized algorithm for aggregate fairness in wireless sensor networks,” in MobiCom ’06

For data-collection applications in sensor networks, it is important to ensure all data sources have equal (or weighted) access to network bandwidth so that the base stations receive a complete picture about the monitored area. We point out the fairness problem in the current design of sensor networks, which may cause extremely biased bandwidth allocations. It is a challenge to design a fully distributed fairness solution due to the lack of global knowledge about the distribution of data sources and their routing paths. This paper proposes a new aggregate fairness model and a localized algorithm (called AFA) that implements the model. AFA is designed to work with any routing protocol. In particular, it allows the packets from a data source to follow an arbitrary set of forwarding paths to the base stations. This flexibility makes it considerably harder to allocate bandwidth fairly among different data sources. AFA solves the problem with only localized operations at the sensors. It is easy to implement, which is an attractive property for sensor networks. Moreover, the algorithm automatically adjusts a sensor’s forwarding rate to avoid packet drops due to downstream congestion, which helps improve energy efficiency. We perform extensive simulations, demonstrating that the proposed algorithm can effectively improve end-to-end fairness