Research Reports
Permanent URI for this collectionhttp://dl.cerist.dz/handle/CERIST/34
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Item Electrical Energy Consumption Control in Buildings Using Wireless Sensor(CERIST, 2018-01-25) Djenouri, Djamel; Laidi, Roufaida; Zizoua, CherifEnergy consumption in residential and commercial buildings has increased dramatically worldwide in the last decade, due to the constant population and economic growth, the proliferation of electronic and consumer appliances. This has dramatic footprint on the environment in terms of carbon emission, in addition to the economic impact. Green and smart building strategies will play a pivotal role to reduce this footprint and maximize economic and environmental performance. These strategies can be integrated into buildings at any stage, from design and construction, to maintenance and renovation. The use of modern Information and Communication Technologies (ICT), notably IoT solutions, for building control is one of the promising strategies for the future. The aim of this project was to explore this domain, and as a first step to develop a wireless sensor networks based solution for monitoring and energy management in offices. A prototype has been targeted as a proof of concept where sensors monitor physical parameters in CERSIT offices (presence of people, ambient light, etc.), and accordingly actuate lighting, air conditioning, etc. This report is a short summery of the different parts developed in this project.Item UDEPLOY: User-Driven Learning for Occupancy Sensors DEPLOYment In Smart Buildings(CERIST, 2017-12-25) Laidi, Roufaida; Djenouri, DjamelA solution for motion sensors deployment in smart buildings is proposed. It diferentiates the monitored zones according to their occupancy, where highly-occupied zones have higher coverage requirements over low-occupied zones, and thus are assigned higher granularity in the targeted coverage (weights). The proposed solution is the rst that de nes a user-driven approach, which uses sampling of occupants' behavior to determine the zones and the coverage weights. The samples are acquired during a short learning phase and then used to derive a graph model. The latter is plugged into a greedy, yet e ective, algorithm that seeks optimal placement for maximizing detection accuracy while reducing the cost (number of sensors). Practical aspects such as the scalability and the applicability of the solution are considered. A simulation study that compares the proposed solution with two state-of-the-art solutions shows the superiority of the proposed approach in the accuracy of detection (increased coverage), and scalability (reduced runtime).Item New GPU-based Swarm Intelligence Approach For Reducing Big Association Rules Space(CERIST, 2017-06-14) Djenouri, Youcef; Bendjoudi, Ahcène; Djenouri, Djamel; Belhadi, Asma; Nouali-Taboudjemat, NadiaThis paper deals with exploration and mining of association rules in big data, with the big challenge of increasing computation time. We propose a new approach based on meta-rules discovery that gives to the user the summary of the rules’ space through a meta-rules representation. This allows the user to decide about the rules to take and prune. We also adapt a pruning strategy of our previous work to keep only the representatives rules. As the meta-rules space is much larger than the rules space, two approaches are proposed for efficient exploitation. The first one uses a bees swarm optimization method in the meta-rules discovery process, which is extended using GPU-based parallel programming to form the second one. The sequential version has been first tested using medium rules set, and the results show clear improvement in terms of the number of returned meta-rules. The two versions have then been compared on large scale rules sets, and the results illustrate the acceleration on the summarization process by the parallel approach without reducing the quality of resulted meta-rules. Further experiments on Webdocs big data instances reveal that the proposed method of pruning rules by summarizing meta-rules considerably reduces the association rules space compared to state-of-the-art association rules mining-based approaches.Item GPU-based Bio-inspired Model for Solving Association Rules Mining Problem(CERIST, 2017-03-06) Djenouri, Youcef; Bendjoudi, Ahcène; Djenouri, Djamel; Commuzi, Marcoproblem with the purpose of extracting the correlations between items in sizeable data instances. According to the state of the art, the bio-inspired approaches proved their usefulness by finding high number of satisfied rules in a reasonable time when dealing with medium size instances. These approaches are unsuitable for large databases and especially for those existing on the web such as the Webdocs instance. Recently, the Graphics Processor Units (GPU) is considered as one of the most used parallel hardware to solve large scientific complex problems. In this paper, we propose a new GPU-based model of the bio-inspired approaches for solving association rules mining problem. Our model benefits from the massively GPU threaded by evaluating multiple rules in parallel on GPU. To validate the proposed model, the most used bio-inspired approaches (GA, PSO, and BSO) have been executed on GPU to solve well-known large ARM instances. Real experiments have been carried out on an Intel Xeon 64 bit quad-core processor E5520 coupled to an Nvidia Tesla C2075 GPU device. The results show that the genetic algorithm outperforms PSO and BSO. Moreover, it outperforms the state-of-the-art GPU-based ARM approaches when dealing with the challenging Webdocs instance.Item Energy Harvesting Aware Minimum Spanning Tree for Survivable WSN with Minimum Relay Node Addition(CERIST, 2016-08-31) Djenouri, Djamel; Bagaa, Miloud; Ali, Chelli; Balasingham, IlangkoSurvivable wireless sensor networks that take advantage of green energy resources from the environment is considered in this paper. The particular problem of constrained relay nodes (RNs) placement to ensure communication coverage in the single-tiered topology while taking advantage of the energy harvesting potentials of sensor nodes (SNs) is dealt with. The contribution is to consider a realistic energy harvesting model where harvesting potentials may vary from one node to another. Without loss of generality, the energy model used in this paper is appropriate to wireless charging, but the proposed solution can be extended to the use of any energy harvesting technology. Based on this model, we propose a heuristic based on spanning tree calculation in an edge weighted graph model where the traffic routed at every node is proportional to its effective energy. RNs are added to help non-leaf nodes in the tree that cannot meet the defined survivability condition. A lower-bound of the proposed model is derived using integer linear programming. The proposed solution is compared by simulation to the single solution from the literature that treats the problem of RNs placement while considering energy harvesting capacity of SNs. A simplified model is used in the simulation to allow comparison. The performance results show that the proposed solution ensures survivability by adding a lower number of RNs.Item An Oscillation-Based Algorithm for Reliable Vehicle Detection with Magnetic Sensors(CERIST, 2016-02-25) Djenouri, Djamel; Doudou, Messaoud; Kafi, Mohamed AmineVehicle monitoring using a wireless sensor network is considered in this paper, where a new algorithm is proposed for vehicle detection with magnetic sensors. The proposed algorithm is based on processing the magnetic signal and thoroughly analyzing the number/direction of its oscillations. The main feature of the proposed algorithm over the state-of-the-art ones is its capability to detect vehicles with different shapes of signatures, while most state-of-the-art algorithms assume regular shapes of signatures. This makes the algorithm effective with all types of magnetic sensors. The proposed algorithm has been implemented on Micaz sensor motes and tested in real word scenarios. Results show reliability beyond 93% in all samples, and more than 95% in most of them.Item Parallel BSO Algorithm for Association Rules Mining using Master/Workers Paradigm(CERIST, 2015-07-07) Djenouri, Youcef; Bendjoudi, Ahcène; Djenouri, DjamelThe extraction of association rules from large transactional databases is considered in the paper using cluster architecture parallel computing. Motivated by both the successful sequential BSO-ARM algorithm, and the strong matching between this algorithm and the structure of the cluster architectures, we present in this paper a new parallel ARM algorithm that we call MW-BSO-ARM for Master/Workers version of BSO-ARM. The goal is to deal with large databases by minimizing the communication and synchronization costs, which represent the main challenges that faces any cluster architecture. The experimental results are very promising and show clear improvement that reaches 300% for large instances. For examples, in big transactional database such as WebDocs, the proposed approach generates 107 satisfied rules in only 22 minutes, while a previous GPU-based approach cannot generate more than 103 satisfied rules into 10 hours. The results also reveal that MWBSO-ARM outperforms the PGARM cluster-based approach in terms of computation time.Item Car Park Management with Networked Wireless Sensors and Active RFID(CERIST, 2015-03-30) Djenouri, Djamel; Karbab, Elmouatezbillah; Boulkaboul, Sahar; Bagula, AntoineThis paper considers automatic car park management, which becomes an inevitable option to rationalize traffic management in modern cities. Integration of networked sensor/ actuator and radio frequency identification (RFID) technologies is explored to enable sophisticated services via the Internet in the emerging internet of things (IoT) context. Based on this integration, we propose a scalable and low-cost car parking framework (CPF). A preliminary prototype implementation and experimentation of some modules of the proposed CFP has been performed. The clustering of sensors (sensing boards) into a single mote using the standard I2C protocol has been explored in the prototype, and experimental results demonstrate considerable reduction in cost and energy consumption.Item A Variant of Connected Dominating Set for Application in Communication Networks(CERIST, 2015-03-30) Djenouri, Djamel; Bagaa, MiloudThis paper considers a variant of the connected dominating set (CDS) problem in a graph G = (V;E). The considered problem consists in minimizing the number of CDS vertices that belong to a subset V ′ in V . As far as we know, this problem has not been treated in the literature. Nevertheless, its resolution would be useful in many communication network applications, such as the selection of relay nodes in heterogenous wireless ad hoc networks where only a subset of powerful nodes (e.g., energy or memory rich nodes) may form the network backbone act as relays, or where it is preferable to select relays from these nodes and minimize the number of non-powerful nodes that act as relays. Replacement of non-powerful nodes might be necessary either at the initialization (after deployment), or during the network lifetime, which justifies the need to minimize their number. The problem is first modeled and reduced to the minimum weighted connected dominating set (WCDS) problem in a vertex weighted graph, and then it is resolved by taking advantage of the simple form of the weight function using integer linear programming (ILP). A heuristic is also proposed for large scale resolution. Simulation results confirms closeness of the proposed heuristic to the optimal solution obtained by the ILP, and scalability of the heuristic.Item Energy Harvesting Aware Relay Node Addition for Power-Efficient Coverage in Wireless Sensor Networks(CERIST, 2015-01-11) Djenouri, Djamel; Bagaa, MiloudThis paper deals with power-efficient coverage in wireless sensor networks (WSN) by taking advantage of energyharvesting capabilities. A general scenario is considered for deployed networks with two types of sensor nodes, harvesting enabled nodes (HNs), and none-harvesting nodes (NHNs). The aim is to use only the HNs for relaying packets, while NHNs use will be limited to sensing and transmitting their own readings. The problem is modeled using graph theory and reduced to finding the minimum weighted connected dominating set in a vertex weighted graph. A limited number of relay nodes is added at the positions close to the NHNs in the resulted set. The weight function ensures minimizing the number of NHNs in the set, and thus reducing the relay nodes to be added. Our contribution is to consider relay node placement (addition) in energy harvesting WSN, where only HNs are used to forward packets. This is to preserve the limited energy of NHNs. Extensive simulation results show that the proposed relay node addition strategy prolongs the network lifetime, from the double, to factors of several tens of times. This is at a reasonable cost in terms of the number of relay nodes added, which is compared to a lower-bound derived in the paper.