Shukor Abd Razak

An overview of data routing approaches for wireless sensor networks.

Recent years have witnessed a growing interest in deploying large populations of microsensors that collaborate in a distributed manner to gather and process sensory data and deliver them to a sink node through wireless communications systems. Currently, there is a lot of interest in data routing for Wireless Sensor Networks (WSNs) due to their unique challenges compared to conventional routing in wired networks. In WSNs, each data routing approach follows a specific goal (goals) according to the application. Although the general goal of every data routing approach in WSNs is to extend the network lifetime and every approach should be aware of the energy level of the nodes, data routing approaches may focus on one (or some) specific goal(s) depending on the application. Thus, existing approaches can be categorized according to their routing goals. In this paper, the main goals of data routing approaches in sensor networks are described. Then, the best known and most recent data routing approaches in WSNs are classified and studied according to their specific goals.

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.

Local coverage measurement algorithm in GPS-free wireless sensor networks

Coverage preservation during a mission is a crucial issue for wireless sensor networks (WSNs). There are numerous methods to measure the coverage globally, such as circular, grid and non-circular models, but only a few algorithms can be used to measure the coverage locally, using a sensor. A local coverage measurement algorithm uses only the location of a sensor and its neighbors to calculate the coverage, either by having the location information or by determining this information. Absolute localization for location-based services determines sensor positions according to the global Cartesian coordinate system, usually with the help of a global positioning system (GPS) device. In some applications, such as local coverage measurement, the sectional position of neighbors related to a sensor is sufficient. For a GPS-free environment, this paper develops a local position estimation algorithm (LPEA), using triangulation rules, which contains estimation and estimation correction procedures. Simulation results demonstrated that the algorithm is superior to previous work on finding the exact location of neighbors. Moreover, the estimation error in finding the location of neighbors in a 100-m wide field is less than 5m whenever a minimum of eight neighbors is available. Furthermore, measuring coverage using the results of this LPEA is nearly identical to results where the locations of all sensors are known. In this paper, the circular model, the Delaunay triangulation (DT) coverage measurement model, was used, where the circular model, the circular model with shadowing effect and the circular probabilistic model are measurable through a DT coverage measurement. Simulation and real device experiments indicated that the algorithm is significantly accurate in terms of the local coverage measurement and accelerates the operation in coverage measurement algorithms in wireless sensor networks.

Interpretative Key Management (IKM), A Novel Framework

Nowadays, we use cryptography keys to secure our communications. One of the common ways for securing data exchanging is via the use of symmetric keys to encipher transmitted data over network. Todays practices for managing keys face many issues in key generation, distribution, and revocation. In this paper we propose interpretative key management method which is simpler than the current practices. Eliminating the need for key storage, the need for key distribution, automatic key revocation, and unique key per session are the main features of the new proposed key management method. Deletion of some steps and replacing some others with new ones helped us to dominate many issues faced with common practices of key management.

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.

Towards providing a new lightweight authentication and encryption scheme for MANET

Mobile Ad hoc Network (MANET) is a wireless technology for mobile nodes. This network is setup on fly without any infrastructure. The mobility nature of this network and the lack of infrastructure make it very challenging to be secured. In this paper, we introduce a formal model for Identity-based RSA (Id-RSA) scheme proven secure in the random oracle model. The proposed scheme relies on establishing fast cryptography operations to enhance the network performance. We compare our scheme with RSA-based Threshold Cryptography scheme (RSA-TC) and ECC-based Threshold Cryptography scheme (ECC-TC) in terms of speed and overheads caused by the security messages. We show that the threshold cryptography operations involved in RSA-TC and ECC-TC schemes cause a lot of overheads and delay. We implement these three schemes using the JAVA-based simulation framework (JIST/SWANS). The results show that our Id-RSA scheme is more suitable for MANET mobility environment that require lightweight and secure solutions.

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.