You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A survey of transport protocols for wireless sensor networks 
Chapter Title:  STCP [1] 
1. Abstract of Cited Paper (BIB001):  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. 
2. Abstract of Cited Paper (BIB002):  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. 
3. Abstract of Cited Paper (BIB003):  Reliable data transport in wireless sensor networks is a multifaceted problem influenced by the physical, MAC, network, and transport layers. Because sensor networks are subject to strict resource constraints and are deployed by single organizations, they encourage revisiting traditional layering and are less bound by standardized placement of services such as reliability. This paper presents analysis and experiments resulting in specific recommendations for implementing reliable data transport in sensor nets. To explore reliability at the transport layer, we present RMST (Reliable Multi-Segment Transport), a new transport layer for Directed Diffusion. RMST provides guaranteed delivery and fragmentation/reassembly for applications that require them. RMST is a selective NACK-based protocol that can be configured for in-network caching and repair. 
4. Abstract of Cited Paper (BIB004):  Wireless sensor networks (WSN) are event based systems that rely on the collective effort of several microsensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. Hence, conventional end-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. However, the absence of reliable transport altogether can seriously impair event detection. Hence, the WSN paradigm necessitates a collective phevent-to-sink reliability notion rather than the traditional end-to-end notion. To the best of our knowledge, reliable transport in WSN has not been studied from this perspective before.In order to address this need, a new reliable transport scheme for WSN, the event-to-sink reliable transport (ESRT) protocol, is presented in this paper. ESRT is a novel transport solution developed to achieve reliable event detection in WSN with minimum energy expenditure. It includes a congestion control component that serves the dual purpose of achieving reliability and conserving energy. Importantly, the algorithms of ESRT mainly run on the sink, with minimal functionality required at resource constrained sensor nodes. ESRT protocol operation is determined by the current network state based on the reliability achieved and congestion condition in the network. If the event-to-sink reliability is lower than required, ESRT adjusts the reporting frequency of source nodes aggressively in order to reach the target reliability level as soon as possible. If the reliability is higher than required, then ESRT reduces the reporting frequency conservatively in order to conserve energy while still maintaining reliability. This self-configuring nature of ESRT makes it robust to random, dynamic topology in WSN. Analytical performance evaluation and simulation results show that ESRT converges to the desired reliability with minimum energy expenditure, starting from any initial network state. 
5. Abstract of Cited Paper (BIB005):  In this paper we propose a distributed and scalable algorithm that eliminates congestion within a sensor network, and that ensures the fair delivery of packets to a central node, or base station. We say that fairness is achieved when equal number of packets are received from each node. Since in general we have many sensors transmitting data to the base station, we consider the scenario where we have many-to-one multihop routing, noting that it can easily be extended to unicast or many-to-many routing. Such routing structures often result in the sensors closer to the base station experiencing congestion, which inevitably cause packets originating from sensors further away from the base station to have a higher probability of being dropped. Our algorithm exists in the transport layer of the traditional network stack model, and is designed to work with any MAC protocol in the data-link layer with minor modifications. Our solution is scalable, each sensor mote requires state proportional to the number of its neighbors. Finally, we demonstrate the effectiveness of our solution with both simulations and actual implementation in UC Berkeley's sensor motes. 
6. Abstract of Cited Paper (BIB006):  Network congestion occurs when offered traffic load exceeds available capacity at any point in a network. In wireless sensor networks, congestion causes overall channel quality to degrade and loss rates to rise, leads to buffer drops and increased delays (as in wired networks), and tends to be grossly unfair toward nodes whose data has to traverse a larger number of radio hops. Congestion control in wired networks is usually done using end-to-end and network-layer mechanisms acting in concert. However, this approach does not solve the problem in wireless networks because concurrent radio transmissions on different "links" interact with and affect each other, and because radio channel quality shows high variability over multiple time-scales. We examine three techniques that span different layers of the traditional protocol stack: hop-by-hop flow control, rate limiting source traffic when transit traffic is present, and a prioritized medium access control (MAC) protocol. We implement these techniques and present experimental results from a 55-node in-building wireless sensor network. We demonstrate that the combination of these techniques, Fusion, can improve network efficiency by a factor of three under realistic workloads. 
7. Abstract of Cited Paper (BIB007):  We present Trickle, an algorithm for propagating and maintaining code updates in wireless sensor networks. Borrowing techniques from the epidemic/gossip, scalable multicast, and wireless broadcast literature, Trickle uses a "polite gossip" policy, where motes periodically broadcast a code summary to local neighbors but stay quiet if they have recently heard a summary identical to theirs. When a mote hears an older summary than its own, it broadcasts an update. Instead of flooding a network with packets, the algorithm controls the send rate so each mote hears a small trickle of packets, just enough to stay up to date. We show that with this simple mechanism, Trickle can scale to thousand-fold changes in network density, propagate new code in the order of seconds, and impose a maintenance cost on the order of a few sends an hour. 
8. Abstract of Cited Paper (BIB008):  Previous research on transport layer protocols for wireless sensor ::: networks (WSNs) has focused on designing protocols specifically ::: targeted for sensor networks. Most sensor networks applications, ::: however, are only useful when connected to an external network. The ::: deployment of TCP/IP in WSNs would enable direct connection between ::: the WSN and external TCP/IP networks. However, TCP performs badly in ::: wireless environments both in terms of throughput and energy ::: efficiency. To overcome these problems in WSNs we have designed ::: Distributed TCP Caching. This mechanism greatly enhances TCP ::: performance by caching TCP segments on the nodes in the sensor network ::: and locally retransmitting lost segments. Our simulations ::: demonstrate that with these enhancements TCP performs well enough to ::: be useful in wireless sensor networks. 
9. Abstract of Cited Paper (BIB009):  There exist several applications of sensor networks wherere liability of data delivery can be critical. While the redundancy inherent in a sensor network might increase the degree of reliability, it by no means can provide any guaranteed reliability semantics. In this paper, we consider the problem of reliable sink-to-sensors data delivery. We first identify several fundamental challenges that need to be addressed, and are unique to a wireless sensor network environment. We then propose a scalable framework for reliable downstream data delivery that is specifically designed to both address and leverage the characteristics of a wireless sensor network, while achieving the reliability in an efficient manner. Through ns2 based simulations, we evaluate the proposed framework. 
10. Abstract of Cited Paper (BIB010):  There is a critical need for new thinking regarding overload traffic management in sensor networks. It has now become clear that experimental sensor networks (e.g., mote networks) and their applications commonly experience periods of persistent congestion and high packet loss, and in some cases even congestion collapse. This significantly impacts application fidelity measured at the physical sinks, even under light to moderate traffic loads, and is a direct product of the funneling effect; that is, the many-to-one multi-hop traffic pattern that characterizes sensor network communications. Existing congestion control schemes are effective at mitigating congestion through rate control and packet drop mechanisms, but do so at the cost of significantly reducing application fidelity measured at the sinks. To address this problem we propose to exploit the availability of a small number of all wireless, multi-radio virtual sinks that can be randomly distributed or selectively placed across the sensor field. Virtual sinks are capable of siphoning off data events from regions of the sensor field that are beginning to show signs of high traffic load. In this paper, we present the design, implementation, and evaluation of Siphon, a set of fully distributed algorithms that support virtual sink discovery and selection, congestion detection, and traffic redirection in sensor networks. Siphon is based on a Stargate implementation of virtual sinks that uses a separate longer-range radio network (based on IEEE 802.11) to siphon events to one or more physical sinks, and a short-range mote radio to interact with the sensor field at siphon points. Results from analysis, simulation and an experimental 48 Mica2 mote testbed show that virtual sinks can scale mote networks by effectively managing growing traffic demands while minimizing the impact on application fidelity. 
11. Abstract of Cited Paper (BIB011):  In wireless sensor networks (WSNs), congestion occurs, for example, when nodes are densely distributed, and/or the application produces high flow rate near the sink due to the convergent nature of upstream traffic. Congestion may cause packet loss, which in turn lowers throughput and wastes energy. Therefore congestion in WSNs needs to be controlled for high energy-efficiency, to prolong system lifetime, improve fairness, and improve quality of service (QoS) in terms of throughput (or link utilization) and packet loss ratio along with the packet delay. This paper proposes a node priority-based congestion control protocol (PCCP) for wireless sensor networks. In PCCP, node priority index is introduced to reflect the importance of each node. PCCP uses packet inter-arrival time along with packet service time to measure a parameter defined as congestion degree and furthermore imposes hop-by-hop control based on the measured congestion degree as well as the node priority index. PCCP controls congestion faster and more energy-efficiency than other known techniques.

Literature Review:
CCF BIB006 Siphon BIB011 Fusion BIB007 PCCP BIB012 Trickle BIB008 CODA BIB003 ARC BIB001 Downstream DTC BIB009 GARUDA BIB010 PSFQ BIB002  RMST BIB004 ESRT BIB005 RBC  Reliability guarantee Transport protocols for WSNs where 0 < β < 1. ARC maintains two independent sets of α and β, respectively, for source traffic and transit traffic in order to guarantee fairness. In contrast, Fusion controls congestion in a stop-and-start nonsmooth manner. In Fusion, neighboring nodes stop forwarding packets to the congested node immediately when congestion is detected and notified. CODA adjusts the sending rate similarly to AIMD, while CCF and PCCP use an exact rate adjustment algorithm. Compared to CCF, PCCP provides priority-based fairness and overcomes the drawbacks from the use of nonwork conservative scheduling. However, there is no rate adjustment in Siphon. When congestion occurs, Siphon redirects traffic to virtual sinks (VSs) that, beside the primary low-power mote radio, have another long-rage radio used as a shortcut or "siphon" to mitigate congestion. Trickle BIB008 uses "polite gossip" to control traffic. In Trickle, each node tries to broadcast a summary of its data periodically. In each period, a node can "politely" suppress its own broadcasting if the number of the same metadata, which this node receives from neighboring nodes, exceeds a threshold. On the other hand, if nodes receive new code or metadata, they can shorten the broadcast period and therefore broadcast the new code sooner. In Trickle, metadata are used to describe the code that sensor nodes use, which is usually smaller in size than the code itself.