In this paper, we describe a scalable and distributed framework for minimizing congestion and assuring reliable data transmissions in event based networks. Event based networks are a particular category of sensor networks on which reports are produced only upon the observation of a specific event. This event should satisfy a pre-specified condition. Whenever this condition is satisfied, a sudden traffic increase occurs which may lead the network into congestion. This is particularly undesirable because the data generated during this situation are of great importance, often critical, to the applications. We propose a novel algorithm which is able to control a congestion situation and which is efficient enough to safely transmit almost all the data, generated by the sensors due to an event, back to the sinks. The algorithm does that without throttling the source nodes' data rate. Throttling the data rate could prove fatal for critical networks, due to the fact that each data packet provides the network with updated information concerning the monitored event.
As Wireless Sensor Networks are evolving to applications where high load demands dominate and performance becomes a crucial factor, congestion remains a serious problem that has to be effectively and efficiently tackled. Congestion in WSNs is mitigated either by reducing the data load or by increasing capacity (employing sleep nodes). In either case due to the energy constraints and low processing capabilities of sensor nodes, congestion control and avoidance algorithms has to be kept as simple and efficient as possible while overhead must be limited. In this paper we propose a novel and simple Dynamic Alternative Path Selection Scheme (DAlPaS) attempting to face congestion by increasing capacity while attempts to maintain performance requirements. DAlPaS can efficiently and adaptively choose an alternative routing path in order to avoid congested nodes, by taking into consideration a number of critical parameters that affect the performance of a WSN while maintaining overhead in minimal levels. Simulation results show that DAlPaS algorithm can perform significant performance achievements over comparable schemes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.