An Application-Tailored MAC Protocol for Wireless Sensor Networks

We describe a data management framework suitable for wireless sensor networks that can be used to adapt the performance of a medium access control (MAC) protocol depending on the query injected into the network. The framework has a\ud completely distributed architecture and only makes use of information available locally to capture information about network traffic patterns. It allows\ud nodes not servicing a query to enter a dormant mode which minimizes transmissions and yet maintain an updated view of the network. We then introduce an Adaptive, Information-centric and Lightweight MAC\ud (AI-LMAC) protocol that adapts its operation depending on the information presented by the framework. Our results demonstrate how transmissions are greatly reduced during the dormant mode. During the active mode, the MAC\ud protocol adjusts fairness to match the expected requirements of the query thus reducing latency. Thus such a data management framework allows the MAC to operate more efficiently by tailoring its needs to suit the requirements of the application

Polyhredral techniques in combinatorial optimization I: theory

Combinatorial optimization problems appear in many disciplines ranging from management and logistics to mathematics, physics, and chemistry. These problems are usually relatively easy to formulate mathematically, but most of them are computationally hard due to the restriction that a subset of the variables have to take integral values. During the last two decades there has been a remarkable progress in techniques based on the polyhedral description of combinatorial problems, leading to a large increase in the size of several problem types that can be solved. The basic idea behind polyhedral techniques is to derive a good linear formulation of the set of solutions by identifying linear inequalities that can be proved to be necessary in the description of the convex hull of feasible solutions. Ideally we can then solve the problem as a linear programming problem, which can be done eciently. The purpose of this manuscript is to give an overview of the developments in polyhedral theory, starting with the pioneering work by Dantzig, Fulkerson and Johnson on the traveling salesman problem, and by Gomory on integer programming. We also present some modern applications, and computational experience

Polyhedral Techniques in Combinatorial Optimization

Combinatorial optimization problems arise in several areas ranging from management to mathematics and graph theory. Most combinatorial optimization problems are compu- tationally hard due to the restriction that a subset of the variables have to take integral values. During the last two decades there has been a remarkable development in polyhedral techniques leading to an increase in the size of several problem types that can be solved by a factor hundred. The basic idea behind polyhedral techniques is to derive a good linear formulation of the set of solutions by identifying linear inequalities that can be proved to be necessary in the description of the convex hull of feasible solutions. The purpose of this article is to give anoverview of the developments in polyhedral theory, starting with the pioneering work by Dantzig, Fulkerson and Johnson on the traveling salesman problem, and by Gomory on integer programming. We also discuss several computational aspects and implementation issues related to the use of polyhedral methods.

Sensitivity Analysis of the Economic Lot-Sizing Problem

In this paper we study sensitivity analysis of the uncapacitated single level economic lot-sizing problem, which was introduced by Wagner and Whitin about thirty years ago. In particular we are concerned with the computation of the maximal ranges in which the numerical problem parameters may vary individually, such that a solution already obtained remains optimal. Only recently it was discovered that faster algorithms than the Wagner-Whitin algorithm exist to solve the economic lot-sizing problem. Moreover, these algorithms reveal that the problem has more structure than was recognized so far. When performing the sensitivity analysis we exploit these newly obtained insights

A Note on "Stability of the Constant Cost Dynamic Lot Size Model" by K. Richter

In a paper by K. Richter the stability regions of the dynamic lot size model with constant cost parameters are analyzed. In particular, an algorithm is suggested to compute the stability region of a so-called generalized solution. In general this region is only a subregion of the stability region of the optimal solution. In this note we show that in a computational effort that is of the same order as the running time of Richter's algorithm, it is possible to partition the parameter space in stability regions such that every region corresponds to another optimal solution

Pricing bridges to cross a river.

We consider a Stackelberg pricing problem in directed, uncapacitated networks. Tariffs have to be defined by an operator, the leader, for a subset of m arcs, the tariff arcs. Costs of all other arcs are assumed to be given. There are n clients, the followers, that route their demand independent of each other on paths with minimal total cost. The problem is to find tariffs that maximize the operator's revenue. Motivated by problems in telecommunication networks, we consider a restricted version of this problem, assuming that each client utilizes at most one of the operator's tariff arcs. The problem is equivalent to pricing bridges that clients can use in order to cross a river. We prove that this problem is APX-hard. Moreover, we show that uniform pricing yields both an m–approximation, and a (1 + lnD)–approximation. Here, D is upper bounded by the total demand of all clients. We furthermore discuss some polynomially solvable special cases, and present a short computational study with instances from France Télécom. In addition, we consider the problem under the additional restriction that the operator must serve all clients. We prove that this problem does not admit approximation algorithms with any reasonable performance guarantee, unless NP = ZPP, and we prove the existence of an n–approximation algorithm.Pricing; Networks; Tariffs; Costs; Cost; Demand; Problems; Order; Yield; Studies; Approximation; Algorithms; Performance;

A branch-and-cut approach for solving line planning problems

An important strategic element in the planning process of a railway operator is the development of a line plan, i.e., a set of routes (paths) in a network of tracks, operated at a given hourly frequency. We consider a model formulation of the line planning problem where total operating costs are to be minimized. This model is solved with a branch-and-cut approach, for which we develop a variety of valid inequalities and reduction methods. A computational study of five real-life instances is included.operations research and management science;

On the design of an energy-efficient low-latency integrated protocol for distributed mobile sensor networks

Self organizing, wireless sensors networks are an emergent and challenging technology that is attracting large attention in the sensing and monitoring community. Impressive progress has been done in recent years even if we need to assume that an optimal protocol for every kind of sensor network applications can not exist. As a result it is necessary to optimize the protocol for certain scenarios. In many applications for instance latency is a crucial factor in addition to energy consumption. MERLIN performs its best in such WSNs where there is the need to reduce the latency while ensuring that energy consumption is kept to a minimum. By means of that, the low latency characteristic of MERLIN can be used as a trade off to extend node lifetimes. The performance in terms of energy consumption and latency is optimized by acting on the slot length. MERLIN is designed specifically to integrate routing, MAC and localization protocols together. Furthermore it can support data queries which is a typical application for WSNs. The MERLIN protocol eliminates the necessity to have any explicit handshake mechanism among nodes. Furthermore, the reliability is improved using multiple path message propagation in combination with an overhearing mechanism. The protocol divides the network into subsets where nodes are grouped in time zones. As a result MERLIN also shows a good scalability by utilizing an appropriate scheduling mechanism in combination with a contention period

Polynomial Time Algorithms For Some Multi-Level Lot-Sizing Problems With Production Capacities

We consider a model for a serial supply chain in which production, inventory, and transportation decisions are integrated, in the presence of production capacities and for different transportation cost functions. The model we study is a generalization of the traditional single-item economic lot-sizing model, adding stationary production capacities at the manufacturer, as well as multiple intermediate storage levels (including the retailer level), and transportation between these levels. Allowing for general concave production costs and linear holding costs, we provide polynomialtime algorithms for the cases where the transportation costs are either linear, or are concave with a fixed-charge structure. In the latter case, we make the additional common and reasonable assumption that the variable transportation and inventory costs are such that holding inventories at higher levels in the supply chain is more attractive from a variable cost perspective. The running times of the algorithms are remarkably insensitive to the number of levels in the supply chain