Institute for Systems Research

As networks grow in size, nodes tendto form clusters geographically and hierarchical routing schemes are morecommonly used. Loss network and reduced load models are often used toapproximate end-to-endcall blocking probabilities, and hence, throughput. However so far all workbeing done in this area is for flat networks with flat routing schemes.

We aim at developing a more efficient approximation method for networksthat have a natural hierarchy and/or when some form of hierarchical routingpolicy is used. We present two hierarchical models in detail for fixedhierarchical routing and dynamic hierarchical routing policies,respectively, via the notion of network abstraction, route segmentation, traffic segregationand aggregation. Computation is done separately within each cluster (local)and among clusters (global), and the fixed point is obtained by iterationbetween local and global computations. We also present numerical resultsfor the first case.

The UT must operate both in full- and half-duplex mode, the latter being desirable when power limitations are imposed. We propose a scheme that achieves this goal and guarantees efficient diversity provision. Constant delay contours on the earth's surface are defined. The problem of reliable time delay acquisition is addressed, in case synchronization is lost. The SBS solves that either by using the known estimate of UT position or by requesting a measurement report by the UT.

The problem of channel allocation appears in cellular networks of every kind. Calls arising in the cell overlap area have access to channels of more than one base station and may choose which base station they will use to establish connection. In that case the problems of base station and channel assignment arise jointly.

We address the problem in a linear cellular network and aim at the minimumnumber of utilized channels. We present two algorithms: The first one expands Load Balancing in clique populations and is Sequential Clique Load Balancing (SCLB). The second one is named Clique Load Balancing with Inverse Water-Filling (CLB-IWF). In a dynamic environment, we unify SCLB and CLB-IWF into CLB-DA, which comprises Dynamic Allocation. CLB-DA is compared with Least Loaded Routing (LLR) policy and with Random Routing policy. We finally deduce that at light loads CLB-DA outperforms LLR, attaining smaller blocking probability, whereas at heavier loads all three policies converge.

The performance metric of interest is the end-to-end call blockingprobability. Blocking probabilities in a loss network have been studiedquite extensively but very few considered multiple traffic classes andrates together with adaptive/state dependent routing.

We propose a fixed-point method, a.k.a. reduced load approximation,to estimate the end-to-end blocking probability in a multihop, multirateloss network with adaptive routing. Simulation results are provided tocompare with that of approximations. The approximation scheme is shownto be asymptotically correct in a natural limiting regime, and it givesconservative estimates of blocking probabilities under heavy trafficload.