Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

Topology control in a sensor network balances load on sensor nodes and increases network scalability and lifetime. Clustering sensor nodes is an effective topology control approach. We propose a novel distributed clustering approach for long-lived ad hoc sensor networks. Our proposed approach does not make any assumptions about the presence of infrastructure or about node capabilities, other than the availability of multiple power levels in sensor nodes. We present a protocol, HEED (Hybrid Energy-Efficient Distributed clustering), that periodically selects cluster heads according to a hybrid of the node residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED terminates in O(1) iterations, incurs low message overhead, and achieves fairly uniform cluster head distribution across the network. We prove that, with appropriate bounds on node density and intracluster and intercluster transmission ranges, HEED can asymptotically almost surely guarantee connectivity of clustered networks. Simulation results demonstrate that our proposed approach is effective in prolonging the network lifetime and supporting scalable data aggregation.

/pdf/heed-a-hybrid-energy-efficient-distributed-clustering-4c3cjgsfv9.pdf

HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks

http://cpham.perso.univ-pau.fr/ENSEIGNEMENT/PAU-UPPA/RESA-M2/Clustering-abasi.pdf

A survey on clustering algorithms for wireless sensor networks

Topology Control (TC) is one of the most important techniques used in wireless ad hoc and sensor networks to reduce energy consumption (which is essential to extend the network operational time) and radio interference (with a positive effect on the network traffic carrying capacity). The goal of this technique is to control the topology of the graph representing the communication links between network nodes with the purpose of maintaining some global graph property (e.g., connectivity), while reducing energy consumption and/or interference that are strictly related to the nodes' transmitting range. In this article, we state several problems related to topology control in wireless ad hoc and sensor networks, and we survey state-of-the-art solutions which have been proposed to tackle them. We also outline several directions for further research which we hope will motivate researchers to undertake additional studies in this field.

/pdf/topology-control-in-wireless-ad-hoc-and-sensor-networks-3e17u396zt.pdf

Topology Control in Wireless Ad Hoc and Sensor Networks

Several popular simulation and emulation environments fail to account for realistic packet forwarding behaviors of commercial switches and routers. Such simulation or emulation inaccuracies can lead to dramatic and qualitative impacts on the results. In this paper, we present a measurement-based model for routers and other forwarding devices, which we use to simulate two different Cisco routers under varying traffic conditions. The structure of our model is device-independent, but requires device-specific parameters. We construct a profiling tool and use it to derive router parameter tables within a few hours. Our preliminary results indicate that our model can approximate the Cisco routers. The compactness of the parameter tables and simplicity of the model makes it possible to use it for high-fidelity simulations while preserving simulation scalability.

/pdf/a-device-independent-router-model-okancgbfxl.pdf

A Device-Independent Router Model

In a multi-service network such as ATM, adaptive data services (such as ABR) share the bandwidth left unused by higher priority services. The network indicates to the ABR sources the fair and efficient rates at which they should transmit to minimize their cell loss. Switches must constantly measure the demand and available capacity, and divide the capacity fairly among the contending connections. In this paper, we propose a new method for determining the "effective" number of active connections, and the fair bandwidth share for each connection. We prove the efficiency and fairness of the proposed method analytically, and use several simulations to illustrate its fairness dynamics and transient response properties.

On determining the fair bandwidth share for ABR connections in ATM networks

We design and implement an efficient on-line approach, FlowMate, for clustering flows (connections) emanating from a busy server, according to shared bottlenecks. Clusters can be periodically input to load balancing, congestion coordination, aggregation, admission control, or pricing modules. FlowMate uses in-band (passive) end-to-end delay measurements to infer shared bottlenecks. Delay information is piggybacked on feedback from the receivers, or, if impossible, TCP or application round-trip time estimates are used. We simulate FlowMate and examine the effects of network load, traffic burstiness, network buffer sizes, and packet drop policies on clustering correctness, evaluated via a novel accuracy metric. We find that coordinated congestion management techniques are more fair when integrated with Flow-Mate. We also implement FlowMate in the Linux kernel v2.4.17 and evaluate its performance on the Emulab testbed, using both synthetic and tcplib-generated traffic. Our results demonstrate that clustering of medium to long-lived flows is accurate, even with bursty background traffic. Finally, we validate our results on the Internet Planetlab testbed.

/pdf/flowmate-scalable-on-line-flow-clustering-1y8medpcti.pdf

FlowMate: scalable on-line flow clustering

A multitude of overlay network designs for resilient routing, multicasting, quality of service, content distribution, storage, and object location have been recently proposed. Overlay networks offer several attractive features, including ease of deployment, flexibility, adaptivity, and an infrastructure for collaboration among hosts. In this paper, we explore cooperation among co-existing, possibly heterogeneous, overlay networks. We design Synergy, a utility-based overlay internetworking architecture that fosters overlay cooperation. Our architecture promotes fair peering relationships to achieve synergism. Results from Internet experiments with cooperative forwarding overlays indicate that our Synergy prototype improves delay, throughput, and loss performance, while maintaining the autonomy and heterogeneity of individual overlay networks.

Synergy: an overlay internetworking architecture

We investigate competitive online algorithms for online convex optimization (OCO) problems with linear in-stage costs, switching costs and ramp constraints. While OCO problems have been extensively studied in the literature, there are limited results on the corresponding online solutions that can attain small competitive ratios. We first develop a powerful computational framework that can compute an optimized competitive ratio based on the class of affine policies. Our computational framework can handle a fairly general class of costs and constraints. Compared to other competitive results in the literature, a key feature of our proposed approach is that it can handle scenarios where infeasibility may arise due to hard feasibility constraints. Second, we design a robustification procedure to produce an online algorithm that can attain good performance for both average-case and worst-case inputs. We conduct a case study on Network Functions Virtualization (NFV) orchestration and scaling to demonstrate the effectiveness of our proposed methods.

Sonia Fahmy

Papers

A Device-Independent Router Model

On determining the fair bandwidth share for ABR connections in ATM networks

FlowMate: scalable on-line flow clustering

Synergy: an overlay internetworking architecture

Competitive Online Convex Optimization with Switching Costs and Ramp Constraints