i -If heterogeneous ad hoc battlefield networks are to scale to hundreds or thousands of nodes, then they must be automatically split into separate network domains. Domains allow routing, QoS and other networking protocols to operate on fewer nodes. This division greatly reduces overall overhead (e.g., routing overhead with n nodes goes from ( )and allows protocols to be tuned to more homogenous conditions [1]. Domain generation (or clustering) can be done using either local or global information. The two approaches are complementary since local domain generation reacts faster, requires less overhead, and is more robust; while global domain generation provides better overall domains. While most existing work has concentrated on local distributed solutions, this paper reports on new global domain generation techniques. In particular we concentrate on the design of good cost functions and efficient optimization algorithms. We show that simple "intuitive" cost functions do not produce good domains; rather we need complex functions with multiple parameters depending on the design goals (e.g., low overhead or low delay). Although existing optimization algorithms are too slow to be useful in a large dynamic network, we show that a modified simulated annealing algorithm, with well chosen cooling schedule, state transition probabilities and stop criteria, produces good quality domains in acceptable time.
A communication network can be modeled as a directed connected graph with edge weights that characterize performance metrics such as loss and delay. Network tomography aims to infer these edge weights from their pathwise versions measured on a set of intersecting paths between a subset of boundary vertices, and even the underlying graph when this is not known. In particular, temporal correlations between path metrics have been used infer composite weights on the subpath formed by the path intersection. We call these subpath weights the Path Correlation Data.In this paper we ask the following question: when can the underlying weighted graph be recovered knowing only the boundary vertices and the Path Correlation Data? We establish necessary and sufficient conditions for a graph to be reconstructible from this information, and describe an algorithm to perform the reconstruction. Subject to our conditions, the result applies to directed graphs with asymmetric edge weights, and accommodates paths arising from asymmetric routing in the underlying communication network. We also describe the relationship between the graph produced by our algorithm and the true graph in the case that our conditions are not satisfied. out to be rather natural -for the reconstruction of a graph from its PCD and present an algorithm to achieve it. In the case when the underlying graph violates the reconstructibility conditions, we describe the result of the algorithm -it turns out to be the "simplest" routing network that produces the observed PCD.Network Tomography and the Inversion Problem. The form of our model and the assumptions we make originate from a body of work developed under the term Network Tomography [19] that seeks to infer link metrics and even the underlying network topology from the measured metric values on paths traversing the network between a set of routers at the network boundary, represented by V B . This setting is similar to other graph reconstruction problems, such as tomography of electrical resistance networks (see, e.g., [8,6]), optical networks [10], and graph reconstruction from Schrödinger-type spectral data (see, e.g., [3,4]). However, in a communication network model there is a single path between given origin and destination, in contrast to the electrical current flowing between two points a resistive medium via all possible paths. In this sense, our model is more similar to combinatorial reconstruction problems [1,15].In many practical cases the communication network metrics are additive in the sense that the sum of metric values over links in a path corresponds to the same performance metric for the path. Examples of additive metrics include mean packet delay, log packet transmission probability, and variances in an independent link metric model. For additive metrics, a putative solution to the network tomography problem attempts to invert a linear relation expression between the set of path metrics D and the link metrics W in the formHere A is the incidence matrix of links over paths, A P, is 1 if path...
Increasing network lifetime by reducing energy consumption across the network is one of the major concerns while designing routing protocols for Mobile Ad-Hoc Networks. In this paper, we investigate the main reasons that lead to energy depletion and we introduce appropriate routing metrics in the routing decision scheme to mitigate their effect and increase the network lifetime. For our routing scheme, we take into consideration multiple layer parameters, such as MAC queue utilization, node degree and residual energy. We integrate our multi-metric routing scheme into OLSR, a standard MANET proactive routing protocol. We evaluate via simulations in NS3 the protocol modifications under a range of different static and mobile scenarios. The main observations are that in static and low mobility scenarios our modified routing protocol leads to a significant increase (5%-20%) in network lifetime compared to standard OLSR and slightly better performance in terms of Packet Delivery Ratio (PDR).
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