Finding the Best QoS Path in a Gilbert Channel Network

Many different types of modern wired and wireless communication links can be mathematically described as discrete- time Gilbert channels. In this extended abstract, we present an exact method of calculating the best path in a network of discrete- time Gilbert channels, each of which is defined as a Markov chain with two states. In the "Good" state of the chain, the channel produces no erasure, and in the "Bad" state of the chain, the channel produces an erasure. Our method relies on a modified version of the Dijkstra's algorithm, which we customize to operate on sets of Gilbert channel parameters, instead of real numbers. We prove that the Gilbert channels obeys a certain set of algebraic properties which makes it compatible with our algorithm

Worst-Case Routing Performance Evaluation of Sensor Networks

Successful sensor network applications depends heavily on the ability of these networks to reliably and reasonably perform under the worst-case scenarios, extreme and unusual events for which many such networks are designed to detect. One of the key performance measures is the network's ability to route measurement data from the sensor nodes to the destination node(s). This paper introduces a general framework with which worst-case routing performance of different sensor networks can be evaluated and compared. Our method can either be used as a design optimization tool, or a decision making tool to select and price contending sensor network designs and applications

Optimal Worst-Case QoS Routing in Constrained AWGN Channel Network

In this paper, we extend the optimal worst-case QoS routing algorithm and metric definition given in [1]. We prove that in addition to the q-ary symmetric and q-ary erasure channel model, the necessary and sufficient conditions defined in [2] for the Generalized Dijkstra's Algorithm (GDA) can be used with a constrained non-negative-mean AWGN channel. The generalization allowed the computation of the worst-case QoS metric value for a given edge weight density. The worst-case value can then be used as the routing metric in networks where some nodes have error correcting capabilities. The result is an optimal worst-case QoS routing algorithm that uses the Generalized Dijkstra's Algorithm as a subroutine with a polynomial time complexity of O(V^3)

Decentralized Decision Making in the Game of Tic-tac-toe

Traditionally, the game of Tic-tac-toe is a pencil and paper game played by two people who take turn to place their pieces on a 3times3 grid with the objective of being the first player to fill a horizontal, vertical, or diagonal row with their pieces. What if instead of having one person playing against another, one person plays against a team of nine players, each of whom is responsible for one cell in the 3times3 grid? In this new way of playing the game, the team has to coordinate its players, who are acting independently based on their limited information. In this paper, we present a solution that can be extended to the case where two such teams play against each other, and also to other board games. Essentially, the solution uses a decentralized decision making, which at first seems to complicate the solution. However, surprisingly, we show that in this mode, an equivalent level of decision making ability comes from simple components that reduce system complexity

Finding the best path in a binary Block Interference network

A binary block interference channel (BIC) is model of binary channels with memory that allows for a mathematically tractable computation of channel capacity. One can easily imagine interconnecting such channels into a network that allows point-to-point communication between any two nodes in the network. Given a pair of network nodes, finding the path with the highest capacity is quite trivial if we can assume that all participating nodes in any path connecting the two nodes can perform coding at arbitrary complexity such that at each link capacity is achieved. However, even if the complexity assumption is not taken into account, in most real-life networks (such as the current Internet), only a minimum amount of coding is performed at the link layer. In most networks, coding is performed five or six layers up in the OSI network model, i.e., on either the presentation or the application layer. Under such realistic circumstances, finding the path with the highest capacity is no longer trivial. In this paper, we propose a solution based on a modified version of the Dijkstrapsilas Algorithm

Worst-Case Routing Performance Metrics for Sensor Networks

Successful integration of pervasive sensor networks in mission critical applications depends on the ability of these networks to cope with and reasonably perform under the worst-case scenarios. One of the key performance measures is the network’s ability to route information from the source node to the intended destination. This paper introduces a general framework with which worst-case routing performance of sensor networks can be evaluated and compared. Ultimately, our method can either be used as a design optimization tool, or a decision making tool to select and price contending sensor network designs

A dynamic graph algorithm for the highly dynamic network problem

A recent flooding algorithm [1] guaranteed correctness for networks with dynamic edges and fixed nodes. The algorithm provided a partial answer to the highly dynamic network (HDN) problem, defined as the problem of devising a reliable message-passing algorithm over a HDN, which is a network – or a network mobility model – where edges and nodes can enter and leave the network almost arbitrarily. In this paper, we relax the flooding algorithms’ assumptions by removing the requirement that the network stays connected at all time, and extend the algorithm to solve the HDN problem where dynamic nodes are also involved. The extended algorithm is reliable: it guarantees message passing to all the destination nodes and terminates within a time bounded by a polynomial function of the maximum message transit time between adjacent nodes, and the maximum number of nodes in the network

Finding the best path in a binary Block Interference network

A binary block interference channel (BIC) is model of binary channels with memory that allows for a mathematically tractable computation of channel capacity. One can easily imagine interconnecting such channels into a network that allows point-to-point communication between any two nodes in the network. Given a pair of network nodes, finding the path with the highest capacity is quite trivial if we can assume that all participating nodes in any path connecting the two nodes can perform coding at arbitrary complexity such that at each link capacity is achieved. However, even if the complexity assumption is not taken into account, in most real-life networks (such as the current Internet), only a minimum amount of coding is performed at the link layer. In most networks, coding is performed five or six layers up in the OSI network model, i.e., on either the presentation or the application layer. Under such realistic circumstances, finding the path with the highest capacity is no longer trivial. In this paper, we propose a solution based on a modified version of the Dijkstrapsilas Algorithm