Low Rate Wireless Sensor Network,IEEE 802.15.4 MAC, Route Discovery, Channel Adaptive Probabilistic Broadcast, Broadcast Storm Problem, Probabilistic scheme.

ABSTRACT

Low Rate Wireless Sensor Networks (LR-WSNs) has become an active research area in the past few years. Broadcasting is the backbone of the route discovery process in on-demand unicast routing protocols in  LR-WSNs. Pure flooding is the simplest and most common broadcasting technique for route discovery in on-demand routing protocols. In pure flooding, the route request (RREQ) packet is broadcasted and each receiving node rebroadcasts it. This continues until the RREQ packet arrives at the destination node. The obvious drawback of pure flooding is excessive redundant traffic that degrades the system performance. This is commonly known as broadcast storm problem (BSP). Several schemes have been proposed to address BSP, one of them of them is the Channel Adaptive Probabilistic Broadcast (CAPB) scheme that adapts the rebroadcast probability dynamically to the current Signal to Interference plus Noise Ratio(SINR) and node density in the neighbourhood. This paper evaluates the CAPB scheme in  LR-WSN  based on the IEEE 802.15.4/ZigBee. The CAPB scheme is implemented in the standard AODV routing protocol to replace the pure flooding based broadcast. Extensive ns-2 simulation results show that the CAPB scheme outperforms the standard AODV and the fixed probablisitic scheme, in terms of routing overhead, throughput, end-to-end delay and energy consumption significantly in noisy LR-WSNs.

INTRODUCTION

The proliferation of applications based on IEEE 802.15.4/Zigbee (like monitoring physical or environmental conditions, such as temperature, sound, vibration and etc) have kept LR-WSN an active area of research over the past two decades. A LR-WSN is a self-configuring, self-healing and infrastructure-less network of mobile nodes connected to each other over single-hop or multi-hop wireless links on ad-hoc basis (Chen et al. 2008). More details about the IEEE 802.15.4/Zigbee can be found in  IEEE802.15.4 2006.

These characteristics of mobile LR-WSNs make them an ideal choice for a number of applications e.g., communications in battlefield, rescue operation in disaster areas or quick deployment of networks without requiring huge infrastructure.

In mobile LR-WSN nodes can be located arbitrarily within an area and are free to move. The movement of LR-WSN nodes changes the network topology dynamically. Mobile LR-WSN nodes adapt to the changing topology by discovering new neighbours and establishing new routes to destination nodes (Yick et al. 2008). A node may not communicate directly with a distant node due to limited transmission range, and may have to rely on other nodes to relay the message along the route to the final destination node. In this way, each node acts as a host node as well as a relay node to extend the reachability of other nodes.

When a node wants to send data to a remote node, first, it finds out a set of relay nodes between itself and the remote node. The process of finding the optimal set of relay nodes between the source node and the destination node is called route discovery. Node mobility, limited battery power and the error-prone nature of wireless links are the main challenges in designing an efficient rout discovery process in LR-WSNs.

A number of routing protocols have been proposed in the literature (Boukerche et al. 2011 and Kulkarni et al. 2011). These protocols generally fall into three categories namely table-driven (proactive), on-demand (reactive) and hybrid routing protocols. Interested reader can find a survey in (Boukerche et al. 2011).

In on-demand routing protocols, the routing process consists of two phases namely route-discovery and route-maintenance. These protocols rely on broadcasting for route discovery. For example, in case of AODV routing protocol, a source node that needs to send data to a destination node triggers route discovery mechanism by broadcasting a special control packet, called Route Request (RREQ), to its neighbours who then rebroadcast the RREQ packet to their neighbours. The process continues until the RREQ packet arrives at the destination node. The destination node sends a control packet called Route Reply (RREP) that follows the path of RREQ in reverse direction and informs the source node that a route has been established. Since every node on receiving the RREQ for the first time rebroadcasts it, it requires T-2 rebroadcasts in a network of T nodes assuming the destination is reachable. This kind of broadcasting is called pure flooding and is depicted briefly in Figure 1 while details can be found in (Lee et al. 2002).

Pure flooding often results in substantial redundant transmissions because a node may receive the same packet from multiple other nodes. This phenomenon, commonly known as the broadcast storm problem (BSP) (Adarbah et al. 2015 and Ni et al. 2002). causes frequent contention and packet collisions leading to increased communication overhead and serious performance complications in densely populated WSNs. BSP equally affects the route maintenance phase during which routes are refreshed by triggering new route discovery requests to replace the broken routes. To address the BSP the Channel Adaptive Probabilistic Broadcasting (CAPB) scheme that adapts the probability of rebroadcasting RREQ packets dynamically according to the thermal noise, co-channel interference and node density in the neighbourhood has been rescently deployed (Adarbah et al. 2015).

This paper evaluate the performance of the CAPB in LR-WSN based on IEEE802.15.4/Zigbee . The CAPB scheme is implemented in the network simulator ns-2 and its performance has been compared with SoA schemes in terms of routing overhead, throughput, end-to-end delay and energy consumption. Simulation results showed that the proposed scheme outperforms the SoA broadcast scheme significantly.

The rest of the paper is organized as follows: Section 2 presents the related work, Section 3 presents the CAPB broadcast scheme, and Section 4 presents simulation results and analysis followed by conclusions in Section 5.

RELATED WORK

There are servel studies for addressing the performance evaluation of routing protocls over IEEE 802.15.4/Zigbee networks have been conducted in the literature (Oliveira & Salazar 2014, Kasraoui et al. 2012 and Cuomo et al. 2007).

Cuomo et al. (2007) and  Kasraoui et al. (2012) evaluated and compared the performance of Zigbee hierarchical routing protocol with On-Demand Routing protocol in terms of end to end delay, delivery ratio and routing overhead based on IEEE 802.15.4/Zigbee network. However, they did not condsider the effect of thermal noise and interfenrce in their study. Oliveira and Salazar (2014) evaluated  the routing protocols in IEEE 802.15.4 standard applied on Wind Farms Monitoring in terms of  packet losses, throughput, end-to-end delay and jitter, without considering the effect of thermal noise plus interference from the lower layer.

To the best of the authors’ knowledge, no previous work on evaluating the routing protocol on IEEE 802.15.4/Zigbee network has considered the effects of thermal noise, co-channel interference, and node density in the neighbourhood simultaneously to address the BSP.

THE CAPB ALGORITHM