Wireless Sensor Networks (WSN) are composed of constrained devices and deployed in unattended and hostile environments. Most papers presenting solutions for WSN evaluate their work over random topologies to highlight some of their "good" performances. They rarely study these behaviors over more than one topology. Yet, the topology used can greatly impact the routing performances. This is what we demonstrate in this paper. We present a study of the impact of network topology on algorithms performance in Wireless Sensor Networks and illustrate it with geographic routing. Geographic routing is a family of routing algorithms using nodes coordinates to route data packet from source to destination. We measure the impact of different network topologies from realistic ones to regular and unrealistic ones through extensive simulations. Studied algorithms are common geographic greedy algorithms with different heuristics from the literature. We show that different topologies can lead to a difference of up to 25% on delivery ratio and average route length and more than 100% on overall cost of transmissions.

Abstract-Clustering in wireless sensor networks is an efficient way to structure and organize the network. It aims to identify a subset of nodes within the network and bind it a leader (i.e. cluster-head). This latter becomes in charge of specific additional tasks like gathering data from all nodes in its cluster and sending them by using a longer range communication to a sink. As a consequence, a cluster-head exhausts its battery more quickly than regular nodes. In this paper, we present BLAC, a novel Battery-Level Aware Clustering family of schemes. BLAC considers the battery-level combined with another metric to elect the cluster-head. It comes in four variants. The cluster-head role is taken alternately by each node to balance energy consumption. Due to the local nature of the algorithms, keeping the network stable is easier. BLAC aims to maximize the time with all nodes alive to satisfy application requirements. Simulation results show that BLAC improves the full network lifetime 3-time more than traditional clustering schemes by balancing energy consumption over nodes and still delivering high data percentage.

To cite this version:Damien Riquet, Gilles Grimaud, Michaël Hauspie. Large-scale coordinated attacks : Impact on the cloud security. Abstract-Cloud Computing has emerged as a model to process large volumetric data. Though Cloud Computing is very popular, cloud security could delay its adoption. Security of the cloud must provide data confidentiality and protection of resources. Such architecture seems to be vulnerable when confronted to distributed attacks also known as large-scale coordinated attacks.In this paper, we study the impact of large-scale coordinated attacks on Cloud Computing and its current security solutions.We experiment the open-source IDS Snort and a commercialized firewall using distributed portscan. Our results show that these security solutions are not designed to detect distributed attacks. Indeed, an attacker who controls about 32 hosts can easily achieve a distributed portscan without being detected.

Clustering in wireless sensor networks is an efficient way to structure and organize the network. It aims at identifying a subset of nodes within the network and binding it to a leader (i.e., cluster head). The leader becomes in charge of specific additional tasks like gathering data from all nodes in its cluster and sending them using a longer range communication to a sink. As a consequence, a cluster head exhausts its battery more quickly than regular nodes. In this paper, we present four variants of BLAC, a novel battery level aware clustering family of schemes. BLAC considers the battery level combined with another metric to elect the cluster-head. The cluster-head role is taken alternately by each node to balance energy consumption. Due to the local nature of the algorithms, keeping the network stable is easier. BLAC aims at maximizing the time with all nodes alive to satisfy the application requirements. Simulation results show that BLAC improves the full network lifetime three times more than the traditional clustering schemes by balancing energy consumption over nodes and still deliveres high data ratio.

Abstract