Sensor networks can be considered distributed computing platforms with many severe constraints including limited CPU speed, memory size, power, and bandwidth. Individual nodes in sensor networks are typically unreliable and the network topology dynamically changes, possibly frequently. Sensor networks can also be considered a form of ad hoc network. However, here also many constraints in sensor networks are different or more severe. Sensor networks also differ because of their tight interaction with the physical environment via sensors and actuators. Due to all of these differences many solutions developed for general distributed computing platforms and for ad hoc networks cannot be applied to sensor networks. Many new and exciting research challenges exist. This paper discusses the state of the art and presents the key research challenges to be solved, some with initial solutions or approaches.

Providing packet-level quality of service (QoS) is critical to support both rate-sensitive and delay-sensitive applications in the bandwidth-constrained, shared-channel, multihop wireless networks. This problem is challenging due to the unique issues such as location-dependent contention, inherent conflict between ensuring fairness and maximizing channel utilization, and the distributed nature of packet scheduling in such networks. In order to address these issues, we have taken a new self-organizing approach to QoS solutions for such networks. In this approach, local decision makers self-organize themselves and coordinate among one another, and collectively achieve the desired global property. Some features of our approach include fully localized design, coordination among local decision makers, intentional and optimized information propagation, scaling property and achievable global property. Two key contributions of this work are: (a) a model-referenced self-organizing design methodology for multihop wireless networks; and (b) a table-driven approach and a backoff-based a pproach to distributed packet scheduling that provides QoS performance bounds in terms of fairness, throughput and delay, maximizes channel spatial reuse, and arbitrates the conict between fairness and maximal channel utilization. Both proposed designs work within the CSMA/CA MAC framework. We also compare the performance of these two approaches through simulations. Our extensive simulation results have confirmed the effectiveness of the proposed design.