Existing works have approached the problem of reliable transport in ad-hoc networks by proposing mechanisms to improve TCP's performance over such networks. In this paper we show through detailed arguments and simulations that several of the design elements in TCP are fundamentally inappropriate for the unique characteristics of ad-hoc networks. Given that ad-hoc networks are typically stand-alone, we approach the problem of reliable transport from the perspective that it is justifiable to develop an entirely new transport protocol that is not a variant of TCP. Toward this end, we present a new reliable transport layer protocol for ad-hoc networks called ATP (ad-hoc transport protocol). We show through ns2 based simulations that ATP outperforms both default TCP and TCP-ELFN.

Abstract — We present a model for the joint design of congestion control and media access control (MAC) for ad hoc wireless networks. Using contention graph and contention matrix, we formulate resource allocation in the network as a utility maximization problem with constraints that arise from contention for channel access. We present two algorithms that are not only distributed spatially, but more interestingly, they decompose vertically into two protocol layers where TCP and MAC jointly solve the system problem. The first is a primal algorithm where the MAC layer at the links generates congestion (contention) prices based on local aggregate source rates, and TCP sources adjust their rates based on the aggregate prices in their paths. The second is a dual subgradient algorithm where the MAC sub-algorithm is implemented through scheduling linklayer flows according to the congestion prices of the links. Global convergence properties of these algorithms are proved. This is a preliminary step towards a systematic approach to jointly design TCP congestion control algorithms and MAC algorithms, not only to improve performance, but more importantly, to make their interaction more transparent.

In a wireless sensor network of N nodes transmitting data to a single base station, possibly over multiple hops, what distributed mechanisms should be implemented in order to dynamically allocate fair and efficient transmission rates to each node? Our interference-aware fair rate control (IFRC) detects incipient congestion at a node by monitoring the average queue length, communicates congestion state to exactly the set of potential interferers using a novel low-overhead congestion sharing mechanism, and converges to a fair and efficient rate using an AIMD control law. We evaluate IFRC extensively on a 40-node wireless sensor network testbed. IFRC achieves a fair and efficient rate allocation that is within 20- 40% of the optimal fair rate allocation on some network topologies. Its rate adaptation mechanism is highly effective: we did not observe a single instance of queue overflow in our many experiments. Finally, IFRC can be extended easily to support situations where only a subset of the nodes transmit, where the network has multiple base stations, or where nodes are assigned different transmission weights.In a wireless sensor network of N nodes transmitting data to a single base station, possibly over multiple hops, what distributed mechanisms should be implemented in order to dynamically allocate fair and efficient transmission rates to each node? Our interference-aware fair rate control (IFRC) detects incipient congestion at a node by monitoring the average queue length, communicates congestion state to exactly the set of potential interferers using a novel low-overhead congestion sharing mechanism, and converges to a fair and efficient rate using an AIMD control law. We evaluate IFRC extensively on a 40-node wireless sensor network testbed. IFRC achieves a fair and efficient rate allocation that is within 20- 40% of the optimal fair rate allocation on some network topologies. Its rate adaptation mechanism is highly effective: we did not observe a single instance of queue overflow in our many experiments. Finally, IFRC can be extended easily to support situations where only a subset of the nodes transmit, where the network has multiple base stations, or where nodes are assigned different transmission weights.

In this paper, we introduce a novel congestion control algorithm for TCP over multihop IEEE 802.11 wireless networks implementing rate-based scheduling of transmissions within the TCP congestion window. We show how a TCP sender can adapt its transmission rate close to the optimum using an estimate of the current 4-hop propagation delay and the coefficient of variation of recently measured round-trip times. The novel TCP variant is denoted as TCP with Adaptive Pacing (TCP-AP). Opposed to previous proposals for improving TCP over multihop IEEE 802.11 networks, TCP-AP retains the end-to-end semantics of TCP and does neither rely on modifications on the routing or the link layer nor requires cross-layer information from intermediate nodes along the path. A comprehensive simulation study using ns-2 shows that TCP-AP achieves up to 84 % more goodput than TCP NewReno, provides excellent fairness in almost all scenarios, and is highly responsive to changing traffic conditions.

TCP performance degrades significantly in mobile ad hoc networks because most of packet losses occur as a result of route failures. Prior work proposed to provide link failure feedback to TCP so that TCP can avoid responding to route failures as if congestion had occurred. However, after a link failure is detected, several packets will be dropped from the network interface queue; TCP will time out because of these losses. It will also time out for ACK losses caused by route failures. In this paper, we propose to make routing protocols aware of lost data packets and ACKs and help reduce TCP timeouts for mobility-induced losses. Toward this end, we present two mechanisms: early packet loss notification (EPLN) and besteffort ACK delivery (BEAD). EPLN seeks to notify TCP senders about lost data packets. For lost ACKs, BEAD attempts to retransmit ACKs at either intermediate nodes or TCP receivers. Both mechanisms extensively use cached routes, without initiating route discoveries at any intermediate node. We evaluate TCP-ELFN enhanced with the two mechanisms using two caching strategies for DSR, path caches and a distributed cache update algorithm proposed in our prior work. We show that TCP-ELFN with EPLN and BEAD significantly outperforms TCP-ELFN under both caching strategies. We conclude that cross-layer information awareness is key to making TCP efficient in the presence of mobility.

Complex interference in static multi-hop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multi-hop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP) which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient, and achieve near optimal goodputs for all the topologies that we study. WCP achieves this level of performance while being extremely easy to implement. Moreover, WCPCap achieves the max-min rates for our topologies, while still being distributed and amenable to real implementation.

Abstract—Significant progress has been made in understanding the behavior of TCP and congestion-controlled traffic over multihop wireless networks. Despite these advances, however, no prior work identified severe throughput imbalances in the basic scenario of mesh networks, in which one-hop flows contend with two-hop flows for gateway access. In this paper, we demonstrate via real network measurements, test-bed experiments, and an analytical model that starvation exists in such a scenario, i.e., the one-hop flow receives most of the bandwidth while the twohop flow starves. Our analytical model yields a solution consisting of a simple contention window policy that can be implemented via mechanisms in IEEE 802.11e. Despite its simplicity, we demonstrate through analysis, experiments, and simulations, that the policy has a powerful effect on network-wide behavior, shifting the network’s queuing points, mitigating problematic MAC behavior, and ensuring that TCP flows obtain a fair share of the gateway bandwidth, irrespective of their spatial locations. I.

In this paper we focus on self-contention – contention between packets of the same transport layer connection along the path from source to destination. We observe that selfcontention plays an important role in degrading TCP performance in multi-hop wireless networks and that the use of the popular IEEE 802.11 MAC protocol exacerbates selfcontention. We propose and study two MAC-layer approaches to alleviate self-contention. The first approach, called quickexchange (QE), is designed with the intent of reducing the effects of inter-flow self-contention (e.g. between packets of the same connection traveling in opposite directions). The design of our second mechanism, called fast-forward (FF), is geared towards decreasing intra-flow self-contention (e.g. between packets of the same connection traveling in the same direction). We simulate and study our proposed schemes and observe that quick-exchange consistently improves network aggregate goodput (by as much as 20 % in string topologies, 15 % in random static scenarios, and 10 % in random mobile scenarios). In contrast to our expectations, fast-forward causes sporadic and often negative effects on goodput for TCP connections. Upon investigation we find that while the MAC is, in some respect, operating more efficiently, as demonstrated by improved UDP throughput; interactions with TCPs congestion control mechanism cause the goodput to degrade. We analyze various effects that cause the respective behaviors with QE and FF in detail.

One of the triumphs of wireline network research of the last decade has been the casting of the Internet congestion control problem within an optimization framework based on utility functions. Such an approach provides a sound understanding of the underlying stability and fairness issues, as well as a post-facto justification of TCP-like additiveincrease multiplicative-decrease (AIMD) algorithms. This paper provides a counter-example showing that the same result cannot be extended to wireless networks, at least not in a straightforward manner. The fundamental difference is that wireless networks are of a broadcast nature. There is no strict notion of a “link,” since transmissions from nearby nodes interfere with each other. Using a simple model of interference in wireless networks, a counter-example of a wireless network is presented in which the congestion control mechanism has an unstable equilibrium point at the desired fair solution. Further, ns-2 simulations of this counter-example manifest an oscillatory behavior. Surprisingly, this oscillatory behavior appears to be fairly typical in wireless networks, with most randomly chosen network examples manifesting it. This loss of stability suggests a possible need for the re-design of wireless TCP and wireless queue management to explicitly account for the wireless nature of the effects of interference.

The Transmission Control Protocol (TCP) was designed to provide reliable end-to-end delivery of data over unreliable networks. In practice, most TCP deployments have been carefully designed in the context of wired networks. Ignoring the properties of wireless Ad Hoc Networks can lead to TCP implementations with poor performance. In order to adapt TCP to Ad hoc environment, improvements have been proposed in the literature to help TCP to differentiate between the different types of losses. Indeed, in mobile or static Ad hoc networks losses are not always due to network congestion, as it is mostly the case in wired networks. In this report, we present an overview of this issue and a detailed discussion of the major factors involved. In particular, we show how TCP can be affected by mobility and lower layers protocols. In addition, we survey the main proposals which aim at adapting TCP to mobile and static Ad hoc environments.