1,932 research outputs found
Reinforcing Reachable Routes
This paper studies the evaluation of routing algorithms from the perspective of reachability routing, where the goal is to determine all paths between a sender and a receiver. Reachability routing is becoming relevant with the changing dynamics of the Internet and the emergence of low-bandwidth wireless/ad-hoc networks. We make the
case for reinforcement learning as the framework of choice to realize reachability routing, within the confines of the current Internet infrastructure. The setting of the reinforcement learning problem offers several advantages,including loop resolution, multi-path forwarding capability, cost-sensitive routing, and minimizing state overhead,
while maintaining the incremental spirit of current backbone routing algorithms. We identify research issues in reinforcement learning applied to the reachability routing problem to achieve a fluid and robust backbone routing framework. This paper also presents the design, implementation and evaluation of a new reachability routing algorithm that uses a model-based approach to achieve cost-sensitive multi-path forwarding; performance assessment of the algorithm in various troublesome topologies shows consistently superior performance over classical reinforcement learning algorithms. The paper is targeted toward practitioners seeking to implement a reachability routing algorithm
Privacy-preserving Cross-domain Routing Optimization -- A Cryptographic Approach
Today's large-scale enterprise networks, data center networks, and wide area
networks can be decomposed into multiple administrative or geographical
domains. Domains may be owned by different administrative units or
organizations. Hence protecting domain information is an important concern.
Existing general-purpose Secure Multi-Party Computation (SMPC) methods that
preserves privacy for domains are extremely slow for cross-domain routing
problems. In this paper we present PYCRO, a cryptographic protocol specifically
designed for privacy-preserving cross-domain routing optimization in Software
Defined Networking (SDN) environments. PYCRO provides two fundamental routing
functions, policy-compliant shortest path computing and bandwidth allocation,
while ensuring strong protection for the private information of domains. We
rigorously prove the privacy guarantee of our protocol. We have implemented a
prototype system that runs PYCRO on servers in a campus network. Experimental
results using real ISP network topologies show that PYCRO is very efficient in
computation and communication costs
Unified Power Management in Wireless Sensor Networks, Doctoral Dissertation, August 2006
Radio power management is of paramount concern in wireless sensor networks (WSNs) that must achieve long lifetimes on scarce amount of energy. Previous work has treated communication and sensing separately, which is insufficient for a common class of sensor networks that must satisfy both sensing and communication requirements. Furthermore, previous approaches focused on reducing energy consumption in individual radio states resulting in suboptimal solutions. Finally, existing power management protocols often assume simplistic models that cannot accurately reflect the sensing and communication properties of real-world WSNs. We develop a unified power management approach to address these issues. We first analyze the relationship between sensing and communication performance of WSNs. We show that sensing coverage often leads to good network connectivity and geographic routing performance, which provides insights into unified power management under both sensing and communication performance requirements. We then develop a novel approach called Minimum Power Configuration that ingegrates the power consumption in different radio states into a unified optimization framework. Finally, we develop two power management protocols that account for realistic communication and sensing properties of WSNs. Configurable Topology Control can configure a network topology to achieve desired path quality in presence of asymmetric and lossy links. Co-Grid is a coverage maintenance protocol that adopts a probabilistic sensing model. Co-Grid can satisfy desirable sensing QoS requirements (i.e., detection probability and false alarm rate) based on a distributed data fusion model
Cellular Automata Applications in Shortest Path Problem
Cellular Automata (CAs) are computational models that can capture the
essential features of systems in which global behavior emerges from the
collective effect of simple components, which interact locally. During the last
decades, CAs have been extensively used for mimicking several natural processes
and systems to find fine solutions in many complex hard to solve computer
science and engineering problems. Among them, the shortest path problem is one
of the most pronounced and highly studied problems that scientists have been
trying to tackle by using a plethora of methodologies and even unconventional
approaches. The proposed solutions are mainly justified by their ability to
provide a correct solution in a better time complexity than the renowned
Dijkstra's algorithm. Although there is a wide variety regarding the
algorithmic complexity of the algorithms suggested, spanning from simplistic
graph traversal algorithms to complex nature inspired and bio-mimicking
algorithms, in this chapter we focus on the successful application of CAs to
shortest path problem as found in various diverse disciplines like computer
science, swarm robotics, computer networks, decision science and biomimicking
of biological organisms' behaviour. In particular, an introduction on the first
CA-based algorithm tackling the shortest path problem is provided in detail.
After the short presentation of shortest path algorithms arriving from the
relaxization of the CAs principles, the application of the CA-based shortest
path definition on the coordinated motion of swarm robotics is also introduced.
Moreover, the CA based application of shortest path finding in computer
networks is presented in brief. Finally, a CA that models exactly the behavior
of a biological organism, namely the Physarum's behavior, finding the
minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From
software to wetware. Springer, 201
Cost Optimization Approach for MANET using Particle Swarm Optimization
This paper present the approach require to increase the QoS of MANET network using particle swarm optimization algorithm. To improve data communication between two nodes we propose an efficient algorithm for AODV protocol using PSO where instead of suppling all default parameter with default value of AODV protocol we try to provide selective parameters with optimum value so that overall requirement of control packet get decrease that in turn result in to increase quality of service parameters of MANET. For the enhancement of reliability and reduction of cost, node speed control mechanism is implemented using PSO, The given method which is use for simulation, reduces the overall loss of data and also make transmission effective. We have also tested the performance of network by changing data rates and the speed of the node
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