Hamida Seba

ECGK: An efficient clustering scheme for group key management in MANETs

Mobile Ad hoc NETworks (or MANETs) are flexible networks that are expected to support emerging group applications such as spontaneous collaborative activities and rescue operations. In order to provide secrecy to these applications, a common encryption key has to be established between group members of the application. This task is critical in MANETs because these networks have no fixed infrastructure, frequent node and link failures and a dynamic topology. The proposed approaches to cope with these characteristics aim to avoid centralized solutions and organize the network into clusters. However, the clustering criteria used in the literature are not always adequate for key management and security. In, this paper, we propose, a group key management framework based on a trust oriented clustering scheme. We show that trust is a relevant clustering criterion for group key management in MANETs. Trust information enforce authentication and is disseminated by the mobility of nodes. Furthermore, it helps to evict malicious nodes from the multicast session even if they are authorized members of the group. Simulation results show that our solution is efficient and typically adapted to mobility of nodes.

Solving the consensus problem in a dynamic group: an approach suitable for a mobile environment

It is now well recognised that the consensus problem is a fundamental problem when one has to implement fault-tolerant distributed services. We extend the consensus paradigm to asynchronous distributed mobile systems prone to disconnection and process crash failures. The paper, first, shows that a consensus problem between mobile hosts is reducible to two agreement problems (a consensus problem and a group membership problem) between fixed hosts. Then, following an approach investigated by Guerraoui and Schiper (see IEEE Transactions on Software Engineering, vol.27, no.1, p.29-41, 2001), the paper uses a genetic consensus service as a basic building block to construct a modular and simple solution.

A Distance Measure for Large Graphs based on Prime Graphs

Abstract Graphs are universal modeling tools. They are used to represent objects and their relationships in almost all domains: they are used to represent DNA, images, videos, social networks, XML documents, etc. When objects are represented by graphs, the problem of their comparison is a problem of comparing graphs. Comparing objects is a key task in our daily life. It is the core of a search engine, the backbone of a mining tool, etc. Nowadays, comparing objects faces the challenge of the large amount of data that this task must deal with. Moreover, when graphs are used to model these objects, it is known that graph comparison is very complex and computationally hard especially for large graphs. So, research on simplifying graph comparison gainedan interest and several solutions are proposed. In this paper, we explore and evaluate a new solution for the comparison of large graphs. Our approach relies on a compact encoding of graphs called prime graphs. Prime graphs are smaller and simpler than the original ones but they retain the structure and properties of the encoded graphs. We propose to approximate the similarity between two graphs by comparing the corresponding prime graphs. Simulations results show that this approach is effective for large graphs.

Performance enhancement of smooth handoff in mobile IP by reducing packets disorder

Smooth handoff was introduced in mobile IP to overcome this problem of packet loss during handoff. However, smooth handoff causes packets sequence disruption during packet forwarding procedure, which may result in degradation of network performance in higher layer protocol. In this paper, we discuss the impact of receiving out-of-sequence packets by the mobile node on TCP and UDP applications and we propose a technique, which minimizes the arrival of out-of-sequence packets to the mobile node. This technique anticipates forwarding of packets from the current foreign agent to the new one while the mobile node initiates its handoff. To evaluate our solution, we use the unstable time period (UTP) when the packet sequence could be mis-ordered. We show that the unstable period in our solution is very low than the unstable time period in classical smooth handoff. Furthermore, we also show that our solution reduces the considerably out-of-sequence packets generated by smooth handoff.

Survey Monitoring in mobile ad hoc networks: A survey

The growing use of small wireless devices is making mobile ad hoc networks indispensable as an effective solution for ubiquitous computing and internet of things. Moreover, these networks are considered as a communication solution for emergency or disaster situations. However, to be usable at this scale, mobile ad hoc networks need to be monitored if not totally at least partially. Monitoring is a network management function that can be achieved inside the network without any external intervention. The purpose of monitoring in such networks is to collect information such as the functional states of the participating nodes and the operational states of the available routes and to report this information to all participating nodes or to some of them according to the network application. This paper outlines the challenges of monitoring over mobile ad hoc networks. We discuss monitoring issues and provide a comprehensive overview of existing monitoring approaches. We present a classification of these approaches based on mobile ad hoc network characteristics, their deployment issues and the way the network is organized. For each approach, we present a brief overview, then we describe the architecture and the proposed protocols; we discuss their advantages and limitations; and we compare the approaches based on common criteria such as message overhead and distribution.

New data aggregation approach for time-constrained wireless sensor networks

A fundamental challenge in the design of wireless sensor networks (WSNs) is to maximize their lifetime especially because they have a limited and non-exchangeable energy supply. One of the most important methods to prolong the lifetime of a WSN is data aggregation. Indeed, data aggregation reduces the number of broadcasts, hence collisions and energy consumption. Many methods has been proposed in the literatures to organize the network for data aggregation like clustering which has been proved to provide the best performance in term of energy saving, aggregation gain and packet delivery accuracy, or structure free which has been proved to perform better than a structure-based data gathering. To benefit all the advantages of these two approaches, we propose a hybrid method that combines multi-level structure-based approaches for time-constrained wireless sensor networks. Simulation results show that our proposed method can improve aggregation gain and energy consumption.

A lightweight key management scheme for wireless sensor networks

The use of wireless sensor networks (WSNs) in any real-world application requires a certain level of security. To provide security of operations such as message exchange, key management schemes have to be well adapted to the particularities of WSNs. This paper proposes a novel key management scheme called SKM for sequence-based key management in WSNs. In SKM, sensor nodes are pre-distributed with the first term and the recursive formula of a numerical sequence. This two tiny pre-distributed information will ensure the establishment of pairwise keys to each sensor node with its neighbors after its deployment with a small amount of computation. The security analysis of SKM shows its efficiency. Simulation results confirm that SKM is lightweight in term of node’s resources and has a good resilience against node compromising attacks compared to the main existing schemes.

An Event-Driven Clustering Scheme for Data Aggregation in Real-Time Wireless Sensor Networks

Data aggregation is a promising method for conserving energy in Wireless Sensor Networks (WSNs). The most efficient approach to aggregation is organizing the network into clusters. However, this approach which achieves good performance in periodic data collecting applications is proved to be inappropriate for event-driven applications, such as real-time data gathering. In fact, in this case maintaining clusters turned to be very expensive in term of message overhead. To deal with this problem, we propose a clustering scheme suitable for event-driven applications. We show that if the structure is adapted to the occurrence of events, structured approaches can provide good results in real-time WSNs. Simulation results show that our approach performs well both in aggregation gain and energy consumption.

A module-based approach for structural matching of process models

The current tendency of information system organizations to work with process models has led to an increase in the importance of the comparison of these models stored in some collection or repository. Comparing process models for similarity or dissimilarity search faces two main challenges: (1) Finding the most relevant/irrelevant process model to a particular process or query of interest, and (2) Decreasing the time complexity to achieve this task. Many approaches have been proposed to improve the relevance of returned processes depending on matching the graphs that represent these processes. This generally turns to a graph matching problem known to be an NP-Hard problem. In this paper, we propose to decompose process model graphs into modules in order to improve the precision of the returned results while keeping a polynomial time complexity of matchmaking. The Modules are sub-parts of the process model that capture the most important sub-structures of the process graph. With these modules, the original process graph can be represented by a tree which is more easier to match. We have evaluated our approach within a benchmark of process graphs. The results of our experiments confirm that our approach obtains more relevant results with less time than a typical graph matching based method.

Querying massive graph data: A compress and search approach

Querying graph data is a fundamental problem that witnesses an increasing interest especially for massive graph databases which come as a promising alternative to relational databases for big data modeling. In this paper, we study the problem of subgraph isomorphism search which consists to enumerate the embedding of a query graph in a data graph. The most known solutions of this NP-complete problem are backtracking-based and result in a high computational cost when we deal with massive graph databases. We address this problem and its challenges via graph compression with modular decomposition. In our approach, subgraph isomorphism search is performed on compressed graphs without decompressing them yielding substantial reduction of the search space and consequently a significant saving in processing time as well as in storage space for the graphs. We evaluated our algorithms on nine real-word datasets. The experimental results show that our approach is efficient and scalable.