Marjan Radi

Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks.

Interference-Aware Multipath Routing Protocol for QoS Improvement in Event-Driven Wireless Sensor Networks

The existing multipath routing protocols for wireless sensor networks demonstrate the efficacy of traffic distribution over multiple paths to fulfill the Quality of Service (QoS) requirements of different applica- tions. However, the performance of these protocols is highly affected by the characteristics of the wireless channel and may be even inferior to the performance of single-path approaches. Specifically, when multiple adjacent paths are being used concurrently, the broadcast nature of wireless channels results in inter-path interference which significantly degrades end-to-end throughput. In this paper, we propose a Low- Interference Energy-efficient Multipath Routing protocol (LIEMRO) to improve the QoS requirements of event-driven applications. In addition, in order to optimize resource utilization over the established paths, LIEMRO employs a quality-based load balancing algorithm to regulate the amount of traffic injected into the paths. The performance gain of LIEMRO compared to the ETX-based single-path routing protocol is 85%, 80%, and 25% in terms of data delivery ratio, end-to-end throughput, and network lifetime, respectively. Fur- thermore, the end-to-end latency is improved more than 60%.

LIEMRO: A Low-Interference Energy-Efficient Multipath Routing Protocol for Improving QoS in Event-Based Wireless Sensor Networks

In the recent years, multipath routing techniques are recognized as an effective approach to improve QoS in Wireless Sensor Networks (WSNs). However, in most of the previously proposed protocols either the effects of inter-path interference are ignored, or establishing low-interference paths is very costly. In this paper, we propose a Low-Interference Energy-efficient Multipath ROuting protocol (LIEMRO) for WSNs. This protocol is mainly designed to improve packet delivery ratio, lifetime, and latency, through discovering multiple interference-minimized node-disjoint paths between source node and sink node. In addition, LIEMRO includes a load balancing algorithm to distribute source node’s traffic over multiple paths based on the relative quality of each path. Simulation results show that using LIEMRO in high traffic load conditions can increase data reception rate and network lifetime even more than 1.5x compared with single path routing approach, while end-to-end latency reduces significantly. Accordingly, LIEMRO is a multipath solution for event-driven applications in which lifetime, reliability, and latency are of great importance.

Modeling low-power wireless communications

Low-power wireless communications have particular characteristics that highly affect the performance of network protocols. However, many of these essential characteristics have not been considered in the existing simulation platforms and analytical performance evaluation models. While this issue invalidates many of the reported evaluation results, it also impedes pre-deployment performance prediction and parameter adjustment. Accordingly, this paper studies, analyzes and proposes models for accurate modeling of low-power wireless communications. Our contributions are six-fold. First, we investigate the essential characteristics of low-power wireless transceivers. Second, we present a classified and detailed study on modeling signal propagation, noise floor, system variations and interference. Third, we highlight the importance and effects of system variations and radio regularity on the real applications of wireless sensor networks. Fourth, we reveal the inaccuracy of the packet reception algorithms used in the existing simulators. Furthermore, we propose an improved packet reception algorithm and we confirm its accuracy through comparison with empirical results. Fifth, we propose an architecture to integrate and implement the models presented in this paper. Finally, we show that the transitional region can be employed by the simulators to confine the propagation range and improve simulation scalability. To the best of our knowledge this is the first work that reveals the essentials of accurate modeling and evaluation of low-power wireless communications.

Improving broadcast reliability for neighbor discovery, link estimation and collection tree construction in wireless sensor networks

Neighbor Discovery and Link Estimation (NDLE) phase and Collection Tree Construction (CTC) phase are essential for correct and efficient operation of network protocols. However, the accuracy of these phases is highly affected by packet collisions, because CSMA is used for access arbitration and it does not support collision avoidance with broadcast transmissions. To improve NDLE accuracy: (i) We propose contention window adjustment mechanisms that rely on collision detection through the capture effect. In contrast to the existing approaches that utilize a long inter-packet duration for collision avoidance, the proposed mechanisms do not depend on network configuration and can provide adaptive collision avoidance with respect to the local collision intensity. (ii) We propose a mathematical model through which the MAC protocol can be configured to achieve a desired broadcasting success probability. (iii) We investigate and show the potential benefits of exploiting partially recovered packets during the NDLE phase. To improve CTC accuracy, we propose the Geowindow algorithm, which reduces packet collisions through contention window size management and transmission prioritization. Our results show that the Geowindow algorithm can improve the efficiency of the TinyOSs Collection Tree Protocol up to 74% in terms of tree cost, without increasing duration or energy consumption. Also, it can improve the packet delivery performance up to 70% in data gathering scenarios. The proposed MAC mechanisms of this paper are not only suitable for the initialization phases, but they can also be used for NDLE and CTC updates during the regular network operation, as well as other broadcast-based traffic patterns.

Network initialization in low-power wireless networks: A comprehensive study

The increasing growth of low-power wireless networks in real-world implementations has intensified the need to develop well-organized key network building blocks. Neighbor discovery, link quality measurementanddatacollectionareamongthefundamentalbuildingblocksofnetworkinitialization process. Over the past decade, network initialization has attracted significant attention from the research community of low-power wireless networks.Accordingly, the general concern of this paper is to survey neighbor discovery, link evaluation and collection tree construction protocols, as well as, research challenges in these research areas. Furthermore, we explore the impacts of these protocols on the functionality of different layers in the network protocol stack. In order to provide a clear view of the state-of-the-art neighbor discovery approaches, this paper also presents a classification of the existing neighbor discovery protocols. Finally, some of the important open issues in developing network initialization protocols are discussed to present new directions for further research.

CAMA: Efficient Modeling of the Capture Effect for Low-Power Wireless Networks

Network simulation is an essential tool for the design and evaluation of wireless network protocols, and realistic channel modeling is essential for meaningful analysis. Recently, several network protocols have demonstrated substantial network performance improvements by exploiting the capture effect, but existing models of the capture effect are still not adequate for protocol simulation and analysis. Physical-level models that calculate the signal-to-interference-plus-noise ratio (SINR) for every incoming bit are too slow to be used for large-scale or long-term networking experiments, and link-level models such as those currently used by the NS2 simulator do not accurately predict protocol performance. In this article, we propose a new technique called the capture modeling algorithm (CAMA) that provides the simulation fidelity of physical-level models while achieving the simulation time of link-level models. We confirm the validity of CAMA through comparison with the empirical traces of the experiments conducted by various numbers of CC1000 and CC2420-based nodes in different scenarios. Our results indicate that CAMA can accurately predict the packet reception, corruption, and collision detection rates of real radios, while existing models currently used by the NS2 simulator produce substantial prediction error.Network simulation is an essential tool for the design and evaluation of wireless network protocols, and realistic channel modeling is essential for meaningful analysis. Recently, several network protocols have demonstrated substantial network performance improvements by exploiting the capture effect, but existing models of the capture effect are still not adequate for protocol simulation and analysis. Physical-level models that calculate the signal-to-interference-plus-noise ratio (SINR) for every incoming bit are too slow to be used for large-scale or long-term networking experiments, and link-level models such as those currently used by the NS2 simulator do not accurately predict protocol performance. In this article, we propose a new technique called the capture modeling algorithm (CAMA) that provides the simulation fidelity of physical-level models while achieving the simulation time of link-level models. We confirm the validity of CAMA through comparison with the empirical traces of the experiments conducted by various numbers of CC1000 and CC2420-based nodes in different scenarios. Our results indicate that CAMA can accurately predict the packet reception, corruption, and collision detection rates of real radios, while existing models currently used by the NS2 simulator produce substantial prediction error.

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

DICSA: Distributed and concurrent link scheduling algorithm for data gathering in wireless sensor networks

Although link scheduling has been used to improve the performance of data gathering applications, unfortunately, existing link scheduling algorithms are either centralized or they rely on specific assumptions that are not realistic in wireless sensor networks. In this paper, we propose a distributed and concurrent link scheduling algorithm, called DICSA, that requires no specific assumption regarding the underlying network. The operation of DICSA is managed through two algorithms: (i) Primary State Machine (PSM): Enables each node to perform its own slot reservation; (ii) Secondary State Machine (SSM): Enables each node to concurrently participate in the slot reservation of its neighbors. Through these algorithms and a set of forbidden slots managed by them, DICSA provides concurrent and collision-free slot reservation. Our results show that the execution duration and energy consumption of DICSA are at least 50% and 40% less than that of DRAND, respectively. In terms of slot assignment efficiency, while our results show higher spatial reuse over DRAND, the maximum slot number assigned by DICSA is at least 60% lower than VDEC. In data-gathering applications, our results confirm the higher performance of DICSA in terms of throughput, delivery ratio and packet delay. We show that the network throughput achievable by DICSA is more than 50%, 70%, 90% and 170% higher than that of DRAND, SEEDEX, NCR and FPS, respectively.

A CROSS -LAYER APPROACH FOR MINIMIZING INTERFERENCE AND LATENCY OF MEDIUM ACCESS IN WIRELESS SENSOR NETWORKS

In low power wireless sensor networks, MAC protocols usually employ periodic sleep/wake schedule to reduce idle listening time. Even though this mechanism is simple and efficient, it results in high end-toend latency and low throughput. On the other hand, the previously proposed CSMA/CA based MAC protocols have tried to reduce inter-node interference at the cost of increased latency and lower network capacity. In this paper we propose IAMAC, a CSMA/CA sleep/wake MAC protocol that minimizes internode interference, while also reduces per-hop delay through cross-layer interactions with the network layer. Furthermore, we show that IAMAC can be integrated into the SP architecture to perform its interlayer interactions. Through simulation, we have extensively evaluated the performance of IAMAC in terms of different performance metrics. Simulation results confirm that IAMAC reduces energy consumption per node and leads to higher network lifetime compared to S-MAC and Adaptive S-MAC, while it also provides lower latency than S-MAC. Throughout our evaluations we have considered IAMAC in conjunction with two error recovery methods, i.e., ARQ and Seda. It is shown that using Seda as the error recovery mechanism of IAMAC results in higher throughput and lifetime compared to ARQ.