Abstract: In future transparent optical networks, it is
important to consider the impact of physical impairments in the
routing and wavelengths assignment process, to achieve efficient
connection provisioning. In this paper, we use classical multi-
objective optimization (MOO) strategies and particularly genetic
algorithms to jointly solve the impairment aware RWA (IA-
RWA) problem. Fiber impairments are indirectly considered
through the insertion of the path length and the number of
common hops in the optimization process. It is shown that
blocking is greatly improved, while the obtained solutions truly
converge towards the Pareto front that constitutes the set of
global optimum solutions. We have evaluated our findings, using
an Q estimator tool, that calculates the signal quality of each path
analytically.
Index Terms RWA, Genetic Algorithm, All-Optical
Networks, Multi Objective Optimization.
Abstract: This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows.
We note that energy balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different type of resources.
Abstract: This paper studies the data gathering problem in wireless networks, where data generated at the nodes has to be collected at a single sink. We investigate the relationship between routing optimality and fair resource management. In particular, we prove that for energy-balanced data propagation, Pareto optimal routing and flow maximization are equivalent, and also prove that flow maximization is equivalent to maximizing the network lifetime. We algebraically characterize the network structures in which energy-balanced data flows are maximal. Moreover, we algebraically characterize communication links which are not used by an optimal flow. This leads to the characterization of minimal network structures supporting the maximal flows.
We note that energy-balance, although implying global optimality, is a local property that can be computed efficiently and in a distributed manner. We suggest online distributed algorithms for energy-balance in different optimal network structures and numerically show their stability in particular setting. We remark that although the results obtained in this paper have a direct consequence in energy saving for wireless networks they do not limit themselves to this type of networks neither to energy as a resource. As a matter of fact, the results are much more general and can be used for any type of network and different types of resources.
Abstract: In this paper a performanse analysis of the packet scheduling switch uses a series of feed forward delays interconnected with elementary optical switches. This series of programmable delay blocks constitute an optical buffer of depth T, whose purpose is to delay/re-arrange incoming packets that request packet contention.Performance results have been obtained for random Bernoulli traffic, Pareto traffic, as well as for smooth with an upper bound of inherent burstiness.
