A survey of transport protocols for wireless sensor networks <s> Design Guidelines <s> We propose PSFQ (Pump Slowly, Fetch Quickly), a reliable transport protocol suitable for a new class of reliable data applications emerging in wireless sensor networks. For example, currently sensor networks tend to be application specific and are typically hard-wired to perform a specific task efficiently at low cost; however, there is an emerging need to be able to re-task or reprogram groups of sensors in wireless sensor networks on the fly (e.g., during disaster recovery). Due to the application-specific nature of sensor networks, it is difficult to design a single monolithic transport system that can be optimized for every application. PSFQ takes a different approach and supports a simple, robust and scalable transport that is customizable to meet the needs of different reliable data applications. To our knowledge there has been little or no work on the design of an efficient reliable transport protocol for wireless sensor networks, even though some techniques found in IP networks have some relevance to the solution space, such as, the body of work on reliable multicast. We present the design and implementation of PSFQ, and evaluate the protocol using the ns-2 simulator and an experimental wireless sensor testbed based on Berkeley motes. We show through simulation and experimentation that PSFQ can out perform existing related techniques (e.g., an idealized SRM scheme) and is highly responsive to the various error conditions experienced in wireless sensor networks, respectively. <s> BIB001 </s> A survey of transport protocols for wireless sensor networks <s> Design Guidelines <s> Event-driven sensor networks operate under an idle or light load and then suddenly become active in response to a detected or monitored event. The transport of event impulses is likely to lead to varying degrees of congestion in the network depending on the sensing application. It is during these periods of event impulses that the likelihood of congestion is greatest and the information in transit of most importance to users. To address this challenge we propose an energy efficient congestion control scheme for sensor networks called CODA (COngestion Detection and Avoidance) that comprises three mechanisms: (i) receiver-based congestion detection; (ii) open-loop hop-by-hop backpressure; and (iii) closed-loop multi-source regulation. We present the detailed design, implementation, and evaluation of CODA using simulation and experimentation. We define two important performance metrics (i.e., energy tax and fidelity penalty) to evaluate the impact of CODA on the performance of sensing applications. We discuss the performance benefits and practical engineering challenges of implementing CODA in an experimental sensor network testbed based on Berkeley motes using CSMA. Simulation results indicate that CODA significantly improves the performance of data dissemination applications such as directed diffusion by mitigating hotspots, and reducing the energy tax with low fidelity penalty on sensing applications. We also demonstrate that CODA is capable of responding to a number of congestion scenarios that we believe will be prevalent as the deployment of these networks accelerates. <s> BIB002 </s> A survey of transport protocols for wireless sensor networks <s> Design Guidelines <s> We consider the issue of designing a generic transport layer protocol for energy-constrained sensor networks. We present the requirements for such a transport protocol and propose sensor transmission control protocol (STCP). STCP is a generic, scalable and reliable transport layer protocol where a majority of the functionalities are implemented at the base station. STCP offers controlled variable reliability, congestion detection and avoidance, and supports multiple applications in the same network. We present the design and implementation of STCP and evaluate the protocol with different scenarios and network characteristics. <s> BIB003
In order to design an efficient transport protocol, several factors must be taken into consideration, including the topology, diversity of applications, traffic characteristics, and resource constraints. The two most significant constrains introduced by WSNs are the energy and fairness among different geographically placed sensor nodes. The transport protocol needs to provide high energy-efficiency and flexible reliability and, if necessary, QoS in terms of throughout, packet loss rate, and end-to-end delay. Therefore, transport protocols for WSNs should have components that include congestion control and loss recovery, since these have a direct impact on energy efficiency, reliability, and application QoS. There are generally two approaches to perform this task. The first would be to design separate protocols or algorithms, respectively, for congestion control and loss recovery. Most existing protocols use this approach and address congestion control or reliable transport separately. With this separate and usually modular design, applications that need reliability can invoke only a loss recovery algorithm, or invoke a congestion control algorithm if they need to control congestion. For example, Congestion Detection and Avoidance (CODA), BIB002 , is a congestion protocol while Pump Slowly Fetch Quickly (PSFQ) BIB001 provides reliable transport. The joint use of these two protocols may provide the full functionality required by the transport protocols for WSNs. In the second approach, design considerations should be taken into account to achieve a full-fledged transport protocol that provides congestion and loss control in an integrated way. For example, Sensor Transmission Control Protocol (STCP) BIB003 implements both congestion control and flexible reliability in a single protocol. For different applications, STCP offers different control policies to both guarantee application requirements and improve energy efficiency. The first approach divides a problem into several subproblems and is more flexible to deal with. The second approach may optimize congestion control and loss recovery, since loss recovery and congestion control in WSNs are often correlated. For example, congestion on contention-based wireless links can lead to packet loss. The combination of CODA and PSFQ may achieve both congestion control and reliability, yet it is not well documented in the literature that such control protocols can be seamlessly integrated in an energy-efficient way. We believe there is a trade-off between an architectural/modular design (the first approach) and an integrated design with performance optimization (the second approach). The same trade-off can also be observed between the traditional protocol stack and the cross-layer optimization.