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The influence of QoS routing on the achievable capacity in TDMA based Ad hoc wireless networks


The issue of providing Quality of Service (QoS) guarantees in an Ad hoc wireless network is a very challenging problem. In this paper, we make the following contributions: (i) analytically derive bounds for the end-to-end call acceptance rate using existing queueing theory methods, (ii) study the impact of the routing scheme on the end-to-end call acceptance rate, and (iii) propose a differentiated services scheme for deterministically providing QoS guarantees. Unlike the existing studies which analyze the transport capacity, we focus on the end-to-end call acceptance. The framework that we assume is that of a TDMA based Ad hoc wireless network. The routing scheme employed influences the end-to-end call acceptance of the network. The metrics that we consider are the call acceptance probability and the system saturation probability (i.e., the probability that the network is in a state in which every new call is rejected). We derive general bounds on the call acceptance and the system saturation for the case of differentiated-classes of users in the network. These bounds indicate the number of calls of the highest priority class that can be admitted into the network. Simulation studies were carried out to study the effect of load, hopcount, and the influence of the routing protocol on the call acceptance. The increase in the call acceptance rate with the introduction of load-balancing highlights the importance of load-balancing in enhancing the system performance. From these studies, we arrive at the following results: (i) load-balancing leads to significant improvement in the end-to-end call acceptance rate, and is an important factor in attaining the maximum end-to-end call acceptance rate in a given network and (ii) it is indeed possible to provide deterministic QoS guarantees for a designated set of nodes which are characterized by “deterministic guarantee limit”.

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  1. 1.

    In the most general case of a model corresponding to K classes of calls in a network having B slots, the Markov process has \(K+B \choose B\) states. This is not a problem for the current analysis since the transitions between the states are restricted: every state has at most 2K neighboring states, and the processes associated with any given regions are decoupled. Further, we are interested in only the steady state of the process and not in the paths traversed. The state-explosion needs to be tackled for an analysis that considers coupled processes or preemptive calls: the interested reader may refer [12] and [13].

  2. 2.

    For the case of preemption, the system can move between certain other states. Corresponding to the case of preemption of a class-2 call by a class-1 call, the system can move from the state (n 1, n 2,…, n K ) to (n 1 + 1, n 2 − 1,…, n K ), n 2 ≥ 1.


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Correspondence to T. Bheemarjuna Reddy.

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Sriram, S., Bheemarjuna Reddy, T. & Siva Ram Murthy, C. The influence of QoS routing on the achievable capacity in TDMA based Ad hoc wireless networks. Wireless Netw 16, 291–310 (2010).

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  • Ad hoc wireless networks
  • QoS routing
  • TDMA
  • Call acceptance probability
  • Load-balancing