The end-to-end throughput of multi-hop communication in wireless ad hoc networks is affected by the conflict between forwarding nodes. It has been shown that sending more packets than maximum achievable end-to-end throughput not only fails to increase throughput but also decreases throughput owing to high contention and collision. Accordingly, it is of crucial importance for a source node to know the maximum end-to-end throughput. The end-to-end throughput depends on multiple factors, such as physical layer limitations, medium access control (MAC) protocol properties, routing policy, and nodes’ distribution. There have been many studies on analytical modeling of end-to-end throughput but none of them has taken routing policy and nodes’ distribution as well as MAC layer altogether into account. In this paper, the end-to-end throughput with perfect MAC layer is obtained based on routing policy and nodes’ distribution in 1-D and 2-D networks. Then, imperfections of IEEE 802.11 protocol are added to the model to obtain precise value. An exhaustive simulation is also made to validate the proposed models using ns-2 simulator. Results show that if the distribution to the next hop for a particular routing policy is known, our methodology can obtain the maximum end-to-end throughput precisely.
Authors in @cite_14 proposed a methodology to obtain maximum end-to-end throughput in a chain topology by creating contention graph corresponding to the topology. However, this method needs the location of all nodes. In @cite_26 , the deviation based method is proposed to obtain end-to-end throughput which uses the central limit theorem to model the throughput deviation. However, as it is shown in @cite_17 , the deviation based model fails to estimate the end-to-end throughput when the number of nodes in a route exceeds 4. Authors in @cite_17 proposed a method to mitigate the deficiencies of the deviation based method which works for even long paths. However, this model requires the location of all nodes which may not be available. In @cite_39 , authors obtained the multi-hop throughput in wireless networks when slotted Aloha and incremental redundancy is used. They assumed that nodes are distributed following Poisson point process and two routing policies, namely furthest neighbor routing and nearest neighbor routing, are studied. They showed that coding and retransmissions provide a fully decentralized MAC protocol. However, their analysis cannot be used for commonly use IEEE 802.11 MAC protocol.
@cite_14 @cite_39 @cite_26 @cite_17
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We evaluate the end-to-end delay of a multihop transmission scheme that includes a source, a number of relays, and a destination, in the presence of interferers located according to a Poisson point process. The medium access control (MAC) protocol considered is a combination of TDMA and ALOHA, according to which nodes located a certain number of hops apart are allowed to transmit with a certain probability. Based on an independent transmissions assumption, which decouples the queue evolutions, our analysis provides explicit expressions for the mean end-to-end delay and throughput, as well as scaling laws when the interferer density grows to infinity. If the source always has packets to transmit, we find that full spatial reuse, i.e., ALOHA, is asymptotically delay-optimal, but requires more hops than a TDMA-ALOHA protocol. The results of our analysis have applications in delay-minimizing joint MAC routing algorithms for networks with randomly located nodes.We simulate a network where sources and relays form a Poisson point process, and each source assembles a route to its destination by selecting the relays closest to the optimal locations. We assess both theoretically and via simulation the sensitivity of the end-to-end delay with respect to imperfect relay placements and route crossings. Understanding the maximum end-to-end throughput available with any given wireless multi-hop network is an important, but very challenging task. It may be approximated up to certain degree for several simplified topologies such as chain, cross, and others. Typically, in case of chain-topology wireless multi-hop networks employing IEEE 802.11 DCF (distributed coordination function), the maximum throughput can be derived by calculating 1-hop average throughput considering the so-called bottleneck region. However, this approximation method that utilizes only the 1-hop average throughput is limited in terms of accuracy. Thus, in this paper, after verifying the limitation of 1-hop average approximation for the throughput calculation of chain-topology multi-hop wireless networks, a refined calculation scheme is proposed by additionally considering the deviation of throughput. Especially, we focus on the fact that the throughput deviation could lead to collisions, and the throughput deviation happens due to the summation of uniformly distributed backoff times of IEEE 802.11 DCF. With several ns-2-based network simulations, we verify the impact of selected temporal variations to the throughput calculation and thus validate the improved accuracy of proposed calculation scheme. In this paper, we present a methodology to analytically compute the throughput capacity, or the maximum end-to-end throughput of a given source and destination pair in a multi-hop wireless network. The end-to-end throughput capacity is computed by considering the interference due to neighboring nodes, as well as various modes of hidden node interference. Knowing the throughput capacity is important because it facilitates the design of routing policy, admission control for realtime traffic, as well as load control for wireless networks. We model location-dependent neighboring interference and we use a contention graph to represent these interference relationships. Based on the contention graph, we formulate the individual link capacity as a set of fixed point equations. The end-to-end throughput capacity can then be determined once these link capacities are obtained. To illustrate the utility of our proposed methodology, we present two important applications: (a) route optimization to determine the path with the maximum end-to-end throughput capacity and, (b) optimal offered load control for a given path so that the maximum end-to-end capacity can be achieved. Extensive simulations are carried out to verify and validate the proposed analytical methodology. In this paper, we address the following question: given a specific placement of wireless nodes in physical space and a specific traffic workload, what is the maximum throughput that can be supported by the resulting network? Unlike previous work that has focused on computing asymptotic performance bounds under assumptions of homogeneity or randomness in the network topology and or workload, we work with any given network and workload specified as inputs.A key issue impacting performance is wireless interference between neighboring nodes. We model such interference using a conflict graph, and present methods for computing upper and lower bounds on the optimal throughput for the given network and workload. To compute these bounds, we assume that packet transmissions at the individual nodes can be finely controlled and carefully scheduled by an omniscient and omnipotent central entity, which is unrealistic. Nevertheless, using ns-2 simulations, we show that the routes derived from our analysis often yield noticeably better throughput than the default shortest path routes even in the presence of uncoordinated packet transmissions and MAC contention. This suggests that there is opportunity for achieving throughput gains by employing an interference-aware routing protocol.