24,920 research outputs found
On wireless network scheduling with intersession network coding
Abstract—Cross-layer optimization including congestion con-trol, routing, and scheduling has shown dramatic throughput improvement over layered designs for wireless networks. In parallel, the paradigm-shifting network coding has empirically demonstrated substantial throughput improvement when coding operations are permitted at intermediate nodes and packets from different sessions are mixed. Designing network codes and the associated flow in network coding presents new challenges for cross-layer optimization for wireless multi-hop networks. This work shows that with a new flow-based characterization of pairwise intersession network coding, a joint optimal scheduling and rate-control algorithm can be implemented distributively. Optimal scheduling is computationally expensive to achieve even in a purely routing-based (without network coding) paradigm, let alone with network coding. Thus, in this paper, the impact of imperfect scheduling is studied, which shows that pairwise intersession network coding can improve the throughput of routing-based solutions regardless of whether perfect/imperfect scheduling is used. Both the deterministic and stochastic packet arrivals and departures are considered. This work shows for the first time a striking resemblance between pairwise intersession network coding and routing, and thus advocates extensions of routing-based wisdoms to their network coding counterpart. Index Terms—Network coding, pairwise intersession network coding, imperfect scheduling, cross-layer optimization, congestion control. I
The Implementation of One Opportunistic Routing in Wireless Networks
In the paper, it proposes an optimization framework addressing fairness issues for opportunity routing in wireless mesh networks, where we use network coding to ease the routing problem. We propose a distributed heuristic algorithm in the case when scheduling is determined by MAC, and discuss the suitability of our algorithm through simulations. It is found that in most situations our algorithm has better performances than the single-path algorithm and the classical network coding which is based opportunity algorithm MORE
Performance analysis for network coding using ant colony routing
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The aim of this thesis is to conduct performance investigation of a combined system of Network Coding (NC) technique with Ant-Colony (ACO) routing protocol. This research analyses the impact of several workload characteristics, on system performance.
Network coding is a significant key development of information transmission and processing. Network coding enhances the performance of multicast by employing encoding operations at intermediate nodes. Two steps should realize while using network coding in multicast communication: determining appropriate transmission paths from source to multi-receivers and using the suitable coding scheme.
Intermediate nodes would combine several packets and relay them as a single packet. Although network coding can make a network achieve the maximum multicast rate, it always brings additional overheads. It is necessary to minimize unneeded overhead by using an optimization technique.
On other hand, Ant Colony Optimization can be transformed into useful technique that seeks imitate the ant’s behaviour in finding the shortest path to its destination using quantities of pheromone that is left by former ants as guidance, so by using the same concept of the communication network environment, shorter paths can be formulated.
The simulation results show that the resultant system considerably improves the performance of the network, by combining Ant Colony Optimization with network coding. 25% improvement in the bandwidth consumption can be achieved in comparison with conventional routing protocols. Additionally simulation results indicate that the proposed algorithm can decrease the computation time of system by a factor of 20%
Computing Bounds on Network Capacity Regions as a Polytope Reconstruction Problem
We define a notion of network capacity region of networks that generalizes
the notion of network capacity defined by Cannons et al. and prove its notable
properties such as closedness, boundedness and convexity when the finite field
is fixed. We show that the network routing capacity region is a computable
rational polytope and provide exact algorithms and approximation heuristics for
computing the region. We define the semi-network linear coding capacity region,
with respect to a fixed finite field, that inner bounds the corresponding
network linear coding capacity region, show that it is a computable rational
polytope, and provide exact algorithms and approximation heuristics. We show
connections between computing these regions and a polytope reconstruction
problem and some combinatorial optimization problems, such as the minimum cost
directed Steiner tree problem. We provide an example to illustrate our results.
The algorithms are not necessarily polynomial-time.Comment: Appeared in the 2011 IEEE International Symposium on Information
Theory, 5 pages, 1 figur
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