Saad Harous

Internet of things: Applications and challenges

The keyword ‘Internet of Things’ (IoT) is used to refer to many concepts related to the extension of the Internet and the Web into the physical daily life. This is supported by means of the widespread of distributed devices with embedded identification, sensing and/or actuation capabilities. IoT envisions a future in which both digital and physical entities can be linked, by means of appropriate information and communication technologies, to enable a big range of applications and services. In this article, I will highlight some details of these technologies, applications and research challenges for IoT.

An efficient clustering protocol increasing wireless sensor networks life time

Due to their rapid and promising development, Wireless Sensor Networks (WSNs) have been predicted to invade all domains in our daily life in the near future. However in order to reach their maturity, researchers must find solution to some difficulties which are slowing down the wide spread use of these networks. These difficulties are inherent to their constrained specificities which require adapted solutions unrelated to classical wire networks. One the activity done by WSN that consumed the most energy is the number of packets sent/received. In order to reduce this number and to ensure WSN successful operation, hierarchical clustering protocols have been developed. In this paper, we present WB-TEEN and WBM-TEEN: two hierarchical routing protocols, based on nodes clustering and improving the well known protocol Threshold sensitive Energy Efficient sensor Network protocol (TEEN). This improvement is accomplished in a way such that each cluster is nodes balanced and the total energy consumption between sensor nodes and cluster heads is minimized by using multi-hops intra-cluster communication. Simulation results (using NS2 simulator) show that the proposed protocols exhibit better performance than Low Energy Adaptive Clustering Hierarchy (LEACH) and TEEN in terms of energy consumption and network lifetime prolongation.

Recognition of handwritten Hindu numerals using structural descriptors

A method for recognizing handwritten Hindi numerals is proposed based on the structural descriptors of a numerals shape. The method consists of three major steps. The first one is preprocessing, where a handwritten numeral is scanned, normalized and then thinned. Next, a robust algorithm is used to segment the scanned image into stroke(s), based on feature points, and to identify cavity features. The output of this algorithm is a syntactic representation (that is one or more syntactic terms). Finally, this syntacytic representation is matched against the set of prototype syntactic representations of handwritten numerals for a possible match. Early experimental results are not only encouraging but also proving the tolerance of the proposed system to recognize a high variability of Hindi numerals shapes. The system attained a successful recognition rate of 96%.

LEACH-CKM: Low Energy Adaptive Clustering Hierarchy protocol with K-means and MTE

The requirement for operation with low energy consumption is one of the major constraints that guide the design of routing protocol in Wireless Sensor Networks (WSN) because each node is powered by a limited and generally an irreplaceable source of energy. In this context, we would like to propose a new protocol which respects the energy constraints, nodes life duration and packets reception. This work is based on the protocol LEACH-C (Low Energy Adaptive Clustering Hierarchy) which uses a centralized architecture to select cluster-heads while involving the base station and the sensors local information. It addresses the isolation problem of remote nodes that fail to communicate their information (coordinates and residual energies) to the base station. This results in an inefficient group formation that leads to a huge loss of data and therefore the network loses its performance. For this, we propose a solution that takes into account the remote nodes during the formation of groups. This new protocol, called LEACH-CKM, uses the K-means classification method to group the nodes and Minimum Transmission Energy routing protocol (MTE) to route information from remote nodes.

Adaptive Multi-path QoS Aware Dynamic Source Routing Protocol for Mobile Ad-Hoc Network

Mobile ad hoc network (MANET) is a collection of mobile nodes interconnected by wireless media. Due to the dynamic topology, several routing algorithms have been proposed to forward data packets between the nodes such as proactive and reactive routing protocols. Quality of services (QoS) in MANET became a challenge and a focus of several researchers. Several approaches have been suggested to improve QoS especially on dynamic source routing (DSR) protocol. In this paper we propose an adaptive multi-path QoS aware dynamic source routing protocol. The protocol will collect information about QoS metrics during the route discovery phase and use them to choose a set of disjoint paths, and distributes the data based on QoS they provide. Each node has to monitor links and adaptively adds or removes paths whenever it is needed to achieve the required QoS. The simulation experiments will be conducted using GloMoSim network simulator. We will compare the performance of the suggested algorithm to the performance of the conventional DSR

SDNHAS: An SDN-Enabled Architecture to Optimize QoE in HTTP Adaptive Streaming

HTTP adaptive streaming (HAS) is receiving much attention from both industry and academia as it has become the de facto approach to stream media content over the Internet. Recently, we proposed a streaming architecture called SDNDASHxa0[1] to address HAS scalability issues including video instability, quality of experience (QoE) unfairness, and network resource underutilization, while maximizing per player QoE. While SDNDASH was a significant step forward, there were three unresolved limitations: 1) it did not scale well when the number of HAS players increased; 2) it generated communication overhead; and 3) it did not address client heterogeneity. These limitations could result in suboptimal decisions that led to viewer dissatisfaction. To that effect, we propose an enhanced intelligent streaming architecture, called SDNHAS, which leverages software defined networking (SDN) capabilities of assisting HAS players in making better adaptation decisions. This architecture accommodates large-scale deployments through a cluster-based mechanism, reduces communication overhead between the HAS players and SDN core, and allocates the network resources effectively in the presence of short- and long-term changes in the network.

Community detection in social networks through similarity virtual networks

Smart marketing models could utilize communities within the social Web to target advertisements. However, providing accurate community partitions in a reasonable time is challenging for current online large-scale social networks. In this paper, we propose an approach to enhance community detection in online social networks using node similarity techniques. We apply these techniques on unweighted social networks to detect community structure. Our proposed approach creates a virtual network based on the original social network. Virtual edges are added during this pre-processing step based on nodes similarity in the original social network. Hence, a virtual link is established between any two similar nodes. Then the landmark CNM algorithm is applied on the generated virtual network to detect communities. This approach, labelled Similarity-CNM is expected to further maximize the quality of the inferred communities in terms of modularity and detection speed. Our experimental evaluation study asserts these gains, which accuracy is supported by a study based on Normalized Mutual Information Measure to determine how similar are the actual communities in the original network and the ones found by the proposed approach in this paper.

A Weight Based Clustering Scheme for Mobile Ad hoc Networks

Mobile Ad hoc networks (MANETs) are self-organizing and self-configuring multi-hop wireless networks without any pre-existing communication infrastructures or centralized management. Scalability in MANETs is a new issue where network topology includes large number of nodes and demands a large number of packets in limited wireless bandwidth and nodes mobility that results in a high frequency of failure regarding wireless links. Clustering in MANETs is an important topic that divides the large network into several sub networks and widely used in efficient network management, improving resource management, hierarchical routing protocol design, Quality of Service and a good monitoring architecture of MANETs security. Subsequently, many clustering approaches have been proposed to divide nodes into clusters to support routing and network management. In this paper, we propose a new efficient weight based clustering algorithm. It takes into consideration the metrics: trust (T), density (D), Mobility (M) and energy (E) to choose locally the optimal cluster heads during cluster formation phase. In our proposed algorithm each cluster is supervised by its cluster head in order to ensure an acceptable level of security. It aims to improve the usage of scarce resources such as bandwidth, maintaining stable clusters structure with a lowest number of clusters formed, decreasing the total overhead during cluster formation and maintenance, maximizing lifespan of mobile nodes in the network and reduces energy consumption. Preliminary simulation experiments are conducted to compare the performance of our algorithm to Lowest ID, Highest Degree and WCA in terms of Average Number of CHs, Average Number of CH Changes, Total Number of Re-affiliations, Clusters Stability and Total Overhead. The initial results show that our scheme performs better than other clustering schemes based on the performance metrics considered.

A fault tolerant routing scheme for hypercubes

An efficient distributed fault‐tolerant routing algorithm for the hypercube is proposed based on the existence of a complete set of node‐disjoint paths between any two nodes. Node failure and repairs may occur dynamically provided that the total number of faulty nodes at any time is less than the node‐connectivity n of the n‐cube. Each node maintains for each possible destination which of the associated node‐disjoint paths to use. When a message is blocked by a node failure, the source node is warned and requested to switch to a different node‐disjoint path. The methods used to identify the paths, to propagate node failure information to source nodes, and to switch from one routing path to another incur little communication and computation overhead. We show that if the faults occur reasonably apart in time, then all messages will be routed on optimal or near optimal paths. In the unlikely case where many faults occur in a short period, the algorithm still delivers all messages but via possibly longer paths. An extension of the obtained algorithm to handle link failures in addition to node failures is discussed. We also show how to adapt the algorithm to n‐ary n‐cube networks. The algorithm can be similarly adapted to any interconnection network for which there exists a simple characterization of node‐disjoint paths between its nodes.

Efficient fingerprint singular points detection algorithm using orientation-deviation features

Abstract. Accurate singular point (SP) detection is an important factor in fingerprint (FP) recognition systems. We propose an algorithm to detect SPs in FP images. Our idea is based on the observation that the orientation field (OF) at the regions containing SPs has high variation, whereas in the other regions, it is smooth. Thus, a pixel-wise descriptor that comprises orientation-deviation (OD)-based features is proposed to measure the OF variation in the local neighborhood of a pixel which we call OF energy. Candidate SPs are characterized by locations where the OF energy function has local gradual maxima. Furthermore, the OD-based descriptor exhibits some advanced topological properties, in particular the descriptor profile tendency, which are highly correlated with the SP type. These properties are used to filter out some spurious SPs. A second refining step based on an extended Poincaré index is then applied to keep only genuine SPs with their information. The proposed algorithm has the ability to accurately detect the classical singularities as well as the arch-type SP. Experiments conducted over the public databases FVC2002 db1 and db2 confirm its accuracy and reliability with a reduced false alarm rate in comparison to other proposed methods.