Congestion in WSN increases the energy dissipation rates of sensor nodes as well as the loss of packets and thereby hinders fair and reliable event detection. We find that one of the key reasons of congestion in WSN is allowing sensing nodes to transfer as many packets as possible. This is due to the use of CSMA/CA that gives opportunistic medium access control. In this paper, we propose an energy efficient congestion avoidance protocol that includes source count based hierarchical and load adaptive medium access control and weighted round robin packet forwarding. We also propose in-node fair packet scheduling to achieve fair event detection. The results of simulation show our scheme exhibits more than 90% delivery ratio even under bursty traffic condition which is good enough for reliable event perception.

This paper presents an autonomous traffic engineering framework, named ATE, a highly efficient data dissemination mechanism for multipath data forwarding in Wireless Sensor Networks (WSNs). The proposed ATE has several salient features. First, ATE utilizes three coordinating schemes: an incipient congestion inference scheme, an accurate link quality estimation scheme and a dynamic traffic diversion scheme. It significantly minimizes packet drops due to congestion by dynamically and adaptively controlling the data traffic over congested nodes and/or poorer quality links, and by opportunistically exploiting under-utilized nodes for traffic diversion, while minimizing the estimation and measurement overhead. Second, ATE can provide with high application fidelity of the network even for increasing values of bit error rates and node failures. The proposed link quality estimation and congestion inference schemes are light weight and distributed, improving the energy efficiency of the network. Autonomous Traffic Engineering has been evaluated extensively via NS-2 simulations, and the results have shown that ATE provides a better performance with minimum overhead than those of existing approaches.

Broadband wireless access networks are promising technology for providing better end user services. For such networks, designing a scheduling algorithm that fairly allocates the available bandwidth to the end users and maximizes the overall network throughput is a challenging task. In this paper, we develop a centralized fair scheduling algorithm for IEEE 802.16 mesh networks that exploits the spatio-temporal bandwidth reuse to further enhance the network throughput. The proposed mechanism reduces the length of a transmission round by increasing the number of non-contending links that can be scheduled simultaneously. We also propose a greedy algorithm that runs in polynomial time. Performance of the proposed algorithms is evaluated by extensive simulations. Results show that our algorithms achieve higher throughput than that of the existing ones and reduce the computational complexity.

Sensor networks that carry heterogeneous traffics and are responsible for reporting very time-critical important events necessitate an efficient and robust data dissemination framework. Designing such a framework, that can achieve both the reliability and delay guarantee while preserving the energy efficiency, namely multi-constrained QoS (MCQoS), is a challenging problem. Although there have been many research works on QoS routing for sensor networks, to the best of our knowledge, no one addresses the above three service parameters all together. In this paper, we propose a new aggregate routing model and a distributed aggregate routing algorithm (DARA) that implements the model for achieving MCQoS. DARA is designed for multi-sink, multipath and location aware network architecture. We develop probabilistic models for multipath reliability constraint, sojourn time of a packet at an intermediary node and node energy consumption. Delay-differentiated multi-speed packet forwarding and in-node packet scheduling mechanisms are also incorporated with DARA. The results of the simulations demonstrate that DARA effectively improves the reliability, delay guarantee and energy efficiency.