Improving Routing Efficiency through Intermediate Target Based Geographic Routing

The greedy strategy of geographical routing may cause the local minimum problem when there is a hole in the routing area. It depends on other strategies such as perimeter routing to find a detour path, which can be long and result in inefficiency of the routing protocol. In this paper, we propose a new approach called Intermediate Target based Geographic Routing (ITGR) to solve the long detour path problem. The basic idea is to use previous experience to determine the destination areas that are shaded by the holes. The novelty of the approach is that a single forwarding path can be used to determine a shaded area that may cover many destination nodes. We design an efficient method for the source to find out whether a destination node belongs to a shaded area. The source then selects an intermediate node as the tentative target and greedily forwards packets to it, which in turn forwards the packet to the final destination by greedy routing. ITGR can combine multiple shaded areas to improve the efficiency of representation and routing. We perform simulations and demonstrate that ITGR significantly reduces the routing path length, compared with existing geographic routing protocols

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

Detecting Non-Line of Sight to Prevent Accidents in Vehicular Ad hoc Networks

There are still many challenges in the field of VANETs that encouraged researchers to conduct further investigation in this field to meet these challenges. The issue pertaining to routing protocols such as delivering the warning messages to the vehicles facing Non-Line of Sight (NLOS) situations without causing the storm problem and channel contention, is regarded as a serious dilemma which is required to be tackled in VANET, especially in congested environments. This requires the designing of an efficient mechanism of routing protocol that can broadcast the warning messages from the emergency vehicles to the vehicles under NLOS, reducing the overhead and increasing the packet delivery ratio with a reduced time delay and channel utilisation. The main aim of this work is to develop the novel routing protocol for a high-density environment in VANET through utilisation of its high mobility features, aid of the sensors such as Global Positioning System (GPS) and Navigation System (NS). In this work, the cooperative approach has been used to develop the routing protocol called the Co-operative Volunteer Protocol (CVP), which uses volunteer vehicles to disseminate the warning message from the source to the target vehicle under NLOS issue; this also increases the packet delivery ratio, detection of NLOS and resolution of NLOS by delivering the warning message successfully to the vehicle under NLOS, thereby causing a direct impact on the reduction of collisions between vehicles in normal mode and emergency mode on the road near intersections or on highways. The cooperative approach adopted for warning message dissemination reduced the rebroadcast rate of messages, thereby decreasing significantly the storm issue and the channel contention. A novel architecture has been developed by utilising the concept of a Context-Aware System (CAS), which clarifies the OBU components and their interaction with each other in order to collect data and take the decisions based on the sensed circumstances. The proposed architecture has been divided into three main phases: sensing, processing and acting. The results obtained from the validation of the proposed CVP protocol using the simulator EstiNet under specific conditions and parameters showed that performance of the proposed protocol is better than that of the GRANT protocol with regard to several metrics such as packet delivery ratio, neighbourhood awareness, channel utilisation, overhead and latency. It is also successfully shown that the proposed CVP could detect the NLOS situation and solves it effectively and efficiently for both the intersection scenario in urban areas and the highway scenario

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial