Load-Balance Energy Aware Ad-Hoc On Demand Multipath Distance Vector Routing Protocol (LBEA-AOMDV) for WSN

Load-Balance Energy Aware Ad-Hoc On Demand Multipath Distance Vector Routing Protocol (LBEA-AOMDV) for WSN

Amany Sarhan (Department of Computers and Control Engineering, Tanta University, Tanta, Egypt), Nawal A. El-Fishawy (Department of Computers Science and Engineering, Faculty of Electronic Engineering, Menoufia University, Al Minufya, Egypt) and Mahmoud M. Shawara (Department of Computers and Control Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt)
DOI: 10.4018/IJWNBT.2018070103
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Nowadays, WSNs have received great importance because they are the best solutions that can be used in harsh environments. The main limitation in WSNs is the node power because the sensor node is battery powered and charging or replacing this battery is not applicable. Moreover, in mission-critical applications, sensor nodes can sense important data and the packet carrying this data must be given higher priority from the routing protocol. Most of the current routing protocols consider the node power but do not consider different paths for different priority data which may cause them to be delayed. This article proposes a load-balance energy aware ad-hoc on demand multipath distance vector (LBEA-AOMDV) protocol for wireless sensor networks, which is a multipath routing protocol, based on the original AOMDV. The proposed protocol shows that the paths are alternatively discovered on basis of an energy metric and instead of using only one path in data transmission, the network load is distributed through different paths. LBEA-AOMDV also uses a priority-based technique in which packets are assigned different priority levels and guided to different paths. The overall simulation results show that LBEA-AOMDV gives better performance when compared with AOMDV in terms of average consumed energy, end-to-end delay, number of dropped packets, average throughput and normalized routing load.
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A Wireless Sensor Network (WSN) is set of self-organized sensor nodes connected together to monitor the area under study (Akyildiz et al., 2002, Basagni et al., 2004 as shown in Figure 1. Sensor nodes can be mobile or stationary nodes, which are able to perform various tasks as in Ge, et al. (2016).

Figure 1.

Wireless sensor network


Each sensor node can sense data from the physical environment, process this data to extract important information, store this information, and communicate with the other nodes through wireless links between them until the packets are received by the base station or sink node as shown in Figure 2. From all processes that sensor nodes can perform, communication is the most power consuming process as mentioned by Khan and Goodridge (2015). Energy is the main limitation of WSN as sensor nodes are battery powered and at the same time, it is not possible to charge or replace these batteries as WSN may be used in mission-critical environments such as military or rescue applications (Toh, 2002). Using energy aware routing protocol will be very helpful in minimizing power consumption, as the routing protocol is responsible for communication, where sensor nodes waste most of their battery power in communication (Mostafaei & Menth, 2018).

Figure 2.

Sensor node processes


In mobile ad-hoc networks, routing protocols are classified into two main categories (Moond, et al., 2014; Taneja & Kush, 2010). The first category is proactive or table-driven routing protocols. In proactive routing protocols, such as Destination Sequenced Distance Vector (DSDV) protocol presented by Perkins and Bhagwat (1994), and Optimized Link State Routing (OLSR) protocol presented by Jacquet, et al. (2001), each node builds a routing table and saves a route for each destination before starting the communication. Routing tables need to be updated to be ready for data forwarding. The second category is reactive routing protocols. Ad-hoc On Demand Distance Vector (AODV) protocol, proposed by Perkins, et al. (2003), and Dynamic Source Routing (DSR) protocol proposed by Johnson and Maltz (1996) and modified by Ali, et al. (2018) are examples of reactive routing protocols in which routes between source and destination are built when there is a need for sending data through it. Reactive routing protocols are more suitable for wireless sensor networks as they reduce the number of messages needed to build the routes, which will consequently reduce power consumption.

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