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In order to guarantee a successful data collection process in wireless sensor networks with mobile sinks (WSN-MS), two primary objectives must be reached: 1) enabling the mobile sink to retrieve the maximum amount of data and 2) making sure that the network operates as long as possible. The first problem has been solved previously by proposing an innovative solution HXMAC. To address the second problem, on which this paper focuses, ambient energy harvesting is used to continuously supply power to each sensor node. Thus, this paper's main contribution is to propose EH-HXMAC (HXMAC with energy harvesting), which is based on all these improvements: seamless handover, duty cycling optimization, and mainly energy harvesting capability. EH-HXMAC has been evaluated using Cooja Contiki simulator. Obtained results based on the evaluation of the proposal EH-HXMAC clearly show its suitability as a good solution to promote unlimited lifetime for WSN-MS.

The paper presents a complex simulation system for demonstrating the evacuation process in a building, whereby people attempt to escape from a dangerous scenario. It is novel in that it integrates a range of different models: agent-based model, social force model, and psychological behaviour with emotions and norms. The method uses the communication network based on the message queuing telemetry transport protocol that assists to gather information from the environment. The paths are modified using feelings and rule-based expert system. The authors conduct some simulations and conclude with recommendations for management of safer environments.

Managing container loading and unloading operations at a container terminal using Intelligent Autonomous Vehicle (IAV) is challenging, especially at intersections in the yard, which are often inevitable. For ensuring efficient and accident-free management of these intersections, the IAV must cooperate by exchanging messages. Due to signal obstruction at these intersections, indirect communication is established through an additional relay node to ensure reliable communication. This paper proposes distributed approach using Unmanned Aerial Vehicle (UAV) connectivity to avoid collision and deadlock between IAV at intersections. Due to the obstacles formed by stacked containers blocking the radio transmissions, the proposed algorithm automatically switches the ongoing communication through the UAV to ensure successful communication at intersections. Thus, the idea of introducing UAV as communication relay in a container terminal is an interesting solution that we have adopted in this work. Simulation techniques are used to evaluate our proposal. The obtained results confirm that our UAV-based approach ensures reliable communication and automated intersections management in the yard while further ensuring the safety of IAV traffic.

Due to the advent of IoT and the increasing interest of billions of Internet users towards video contents, a huge multimedia flows has been generated, and as a consequence, a massive load is applied on the underlying core network. This change can affect the network stability and lead to potential performance degradation (such as congestion and delays). This is because multimedia flows are hungry in bandwidth, and also the classical routing protocols currently used in IoT core network (like OSPF) are not adapted yet to support the heavy and the large scale of multimedia traffics with a good quality of service (QoS). In this paper, we introduce the multicommodity-based routing by proposing two contributions, Maximum Concurrent Flow Protocol (MCFPr) and Cache-based Maximum Concurrent Flow (C-MCF). They are conceived based on the Maximum Concurrent Flow approach in order to optimize the routing of multimedia data in the backbone of IoT networks. Both contributions are studied and compared with the state-of-art approaches under different scenarios showing good results, especially in the number of data packets sent (improvement by 50%), and in the transmission time (50% faster compared to the majority), which makes them promising solutions for a rapid and efficient routing in IoT core networks.

Energy is the most important resource in the design of wireless sensor networks (WSNs); as a result, most of the research work was done on this topic. It has been proven that the mobility in this kind of network plays an important role in energy conservation. The movement of the Sink is the most interesting type of mobility. In this work, the authors optimise the Sink travel in sensor field using Hilbert curve as an efficient data collection trajectory. The sensor field is organised in clusters and a virtual rendezvous point (VRP) is selected at each cluster for the sojourn of the Sink. The optimal position of the VRP is obtained using their integer linear program which takes into account the optimal transmission range between the Sink and the sensor node. The obtained results showed the supremacy of the Hilbert curve compared to other curves generated by other optimisation approaches and confirm that the solution based on clustering and Hilbert curve has performed well in terms of energy gain.

The new concept of the Internet of Things (IoT) is bringing new forms of knowledge and applications that rely on smart objects able to sense and process the collected data on a remote workflow server in the perspective to generate automated decisions. In this context, one of the main problems is how to schedule the data flow circulating between objects, and between objects applications. The cooperation between these objects is a promising solution to meet this challenge. Business process management (BPM) is the most adapted way to carry out data management thanks to workflow processes. To this end, a new semantics operator which the authors call a gateway for intelligent process scheduling of IoT (GIPSIT) is proposed as a semantic gateway enabling the management of data flows circulating between the connected objects of IoT. The researchers validate their approach based on GIPSIT operator by implementing a realistic eHealth based-scenario in a Smart Home. The obtained findings showed clearly the importance of this new operator in the context of IoT.

International audience; Nowadays, the massive proliferation of real-world multimedia devices has paved the way to the emergence of a new paradigm called the Internet of Multimedia Things wherein Low-power and Lossy Networks (LLNs) are the main components of this new technology. RPL is an IPv6 routing protocol for LLNs designed by IETF to meet the requirements of a wide range of LLN applications such as Wireless Multimedia Sensor Networks where video traffic is expected to reach 6 times more than non-video traffic in 2025. The mono-instance version of RPL is far from satisfying the network’s Quality of Service (QoS) and the user’s Quality of Experience (QoE), as video in its compressed form is typically composed of various frames with different priorities requiring different QoS and QoE levels. In this paper, we exploit the multi-instance version of RPL for developing a new routing approach that improves the transport of a compressed video, composed of two types of frames with different priorities, by delivering each of them on the corresponding instance. The fundamental question we are addressing, is to find the best way to construct these instances: instances with Nodes Disjoint (ND) or Links Disjoint (LD). To do so, we designed a Multi-Instance routing protocol, named MI-RPL, and we performed extensive simulation experiments using the Cooja simulator. The comparison of MI-RPL-ND, MI-RPL-LD and RPL which regards to QoS and QoE performance metrics, confirms that multi-instance routing for video transmission in WMSN (and in particular MI-RPL-ND) is the best choice.

Agricultural areas are getting reduced due to human negligence in providing modern irrigation methods. As a result, reflections aiming to save water use in the water network management context have been developed over the years. In this chapter, the authors propose a platform for precision agriculture which allows collecting fundamental physical phenomena (soil moisture, air temperature, humidity, water level, water flow, luminous intensity) required for the precision agriculture, which will be carried out to calculate the water quantity needed for optimal irrigation. The platform consists of a sensor/actuator node, a desktop application, and a gateway switches relay that controls the water pump according to the requirement. It uses an algorithm developed with threshold values of temperature and soil moisture (Rawls and Turq formulas) to control water quantity. The proposal is a good starting point for a smart, sustainable, and low-cost irrigation solution.

Smart farming allows to analyze the growth of plants and to influence the parameters of our system in real time in order to optimize plant growth and support the farmer in his activity. Internet of Things (IoT) arrangements, based on the application particular sensors data measurements and intelligent processing, are bridging the holes between the cyber and physical worlds. In this paper, we propose the design and the experiment of a smart farming system based on an intelligent platform which enables prediction capabilities using artificial intelligence (AI) techniques. This system is based on the technology of wireless sensor networks and its implementation requires three main phases, i) data collection phase using sensors deployed in an agricultural field, ii) data cleaning and storage phase, and iii) predictive processing using some AI methods.

International audience; The Internet of Things (IoT) is a network of billion of objects. Data streaming over IoT network is a tedious task that requires intelligent flow management and steering. In this paper, we propose a Distributed Maximum Concurrent Flow (DMCF) algorithm to solve the problem of distributing massive IoT video/data to large consumers over IP/data-centric networks. We propose two approaches based on graph theories, and using reinforcement learning techniques. The proposed approaches are implemented and evaluated over different complex graphs. Results show that in large graphs, reinforcement learning methods outperform classical graph theoretic ones.

Maximizing the network lifetime and data collection are two major functions in WSN. For this aim, mobility is proposed as a solution to improve the data collection process and promote energy efficiency. In this paper, we focus on Sink mobility which has the role of data collection. The problem is how to find an optimal data collection trajectory for the Mobile Sink using approximate optimization techniques. To address this challenge, we propose an optimization model for the Mobile Sink to improve the data collection process and thus to extend the network lifetime of WSN. Our proposition is based on a multiobjective function using a Weighted Sum Method (WSM) by adapting two metaheuristics methods, Tabu Search (TS) and Simulated Annealing (SA), to this problem. To test our proposal by experiment, we designed and developed an Integrated Environment of Optimization and Simulation based on metaheuristics tool (IEOSM). The environment IEOSM helps us to determine the best optimization method in terms of optimal trajectory, execution time, and quality of data collection. The IEOSM also integrates a powerful simulation tool to evaluate the methods in terms of energy consumption, data collection, and latency.

Providing successful data collection in transmitter-initiated wireless sensor networks with mobile Sink (WSN-MS) scenarios is a primary goal of a myriad of critical applications in real world. Unfortunately, the problem of broken links which may occur during data transmission between a source node and a mobile Sink may cause inevitably incomplete data collection. To overcome this challenging issue, we propose in this paper a seamless handover mechanism performed on asynchronous duty cycled MAC protocol on the basis of neighborhood information. By measuring continuously the signal quality of ACKnowledgment messages of transmitted Data during a 1-hop communication, this mechanism allows the source node to continue transmitting data to the mobile Sink using a suitable neighbor node as relay in the case where the Sink node leaves the radio range in direction of that neighbor node. The asynchronous protocol XMAC (without handover) has been chosen as a basic protocol on which we designed our contribution named HXMAC (XMAC with handover). The later was implemented and evaluated using a powerful simulation tool. Experimental results based on the comparison between HXMAC and XMAC clearly showed that handover mechanism is a suitable technique to promote significantly reliability in WSN-MS data collection operation.

International audience; Maximum Concurrent Flow techniques try to combine a maximum flow graph resolution and the satisfaction of queries on this graph. They are proven to give better performance over classical heuristic data-source placement methods combined with greedy query resolution. A new version of the MCF approach is proposed and examined. It is tailored to provide MCF properties for large IoT networks. The results found from evaluation and comparison with other algorithms show that it has high efficiency and outperforms many recent solutions.

Agricultural sector is one of the trademarks of Algeria’s economy. Agriculture plays a vital role in the development of the country. But in today’s world, agricultural areas are getting reduced due to laziness of mankind in irrigation. But due to population growth and overexploitation, the demand for water is exceeding supply. An algorithm was developed with threshold values of temperature and soil moisture (Rawls and Turq formulas) that was programmed into a microcontroller-based gateway to control water quantity. In this paper, we implement a platform for precision agriculture which allows to collect fundamental physical phenomena (the moisture of the soil, air temperature, humidity, water level, water flow, luminous intensity) required for the precision agriculture, which will be treated to calculate the need for water needed for optimal irrigation. Our platform consists of a sensor/actuator node, a desktop application and a gateway switches relay which controls water pump according to the requirement. Our system is a good starting point for a smart irrigator. Arduino (open source) is used in the design of the prototype model in making the system compact and sustainable.

International audience; Wireless sensor networks (WSNs) find extensive applications in various sensitive domains such as tracking, monitoring, environmental data collection and border surveillance. In these cases, the collected data are considered as a critical resource and used to detect any anomalies or abnormal behavior, providing information about an occurring event or a node failure. An outlier detection process must be set up to ensure the proper functioning of the monitoring system. The existing approaches are limited by assumptions on a specific distribution or a predefined data range of the collected data. Often these assumptions do not hold in practice, the data distribution is not known or determining reliable upper and lower bounds for the set of data is not possible. To overcome this, we propose a new copula-based probabilistic multivariate outlier detection method for faulty node detection in wireless sensor networks (WSNs). The joint probability density function of the copula is constructed considering dependency among the captured n−sensed measures without making any assumptions on the distribution of the collected data. The samples having probabilities violating a predetermined control limit are classified to be faulty. The performance of the proposed technique is observed to be better than the existing statistical methods.

International audience; This paper presents a cross-layer communication protocol for Wireless Sensor Network (WSN) enabled surveillance system for sensitive fenced areas, e.g., nuclear/oil site. Initially, the proposed protocol identifies the boundary nodes of the deployed WSN to be used as sentinel nodes, i.e., nodes that are always in active state. The remaining nodes are used as duty-cycled relay nodes during the data communication phase. The boundary nodes identification process and data routing are both performed using an enhanced version of the Greedy Perimeter Stateless Routing (GPSR) protocol, which relies on a Non Unit Disk Graph (N-UDG) and referred to as GPSR over Symmetrical Links (GPSR-SL). Both greedy and perimeter modes of GPSR-SL forward data through symmetrical links only. Moreover, we apply the Mutual Witness (MW) fix to the Gabriel Graph (GG) planarization, to enable a correct perimeter routing on a N-UDG. Simulation results show that the proposed protocol achieves higher packet delivery ratio by up to 3.63%, energy efficiency and satisfactory latency when compared to the same protocol based on the original GPSR.

L'IdO est le moyen d'interconnecter des objets intelligents, capables de collecter des donnees via des capteurs et de prendre des decisions appropriees. Les donnees collectees tout comme les traitements peuvent s'effectuer localement au niveau de ces objets, comme ils peuvent etre externalises sur le Cloud compte tenu des capacites de ce dernier theoriquement illimitees. Dans ce contexte, l'une des difficultes majeures est l'ordonnancement du transfert des donnees entre objets et/ou dans le Cloud. Ce challenge est comparable a celui de la gestion des processus metier (BPM) dans les entreprises, dont la gestion des donnees est conduite souvent par des processus Workflow en raison de leur efficacite en termes d'automatisation, d'optimisation et d'ordonnancement. Ces processus sont modelises a l'aide de methodes telle que la methode BPMN (Business Process Modeling Notation) qui repose sur trois elements pour la modelisation : les tâches, les evenements et les passerelles. Ce dernier element est represente par des operateurs de controle de flux tels que : AND, OR et XOR qui sont destines aux processus d'entreprises, et qui sont limites au traitement de plusieurs cas de processus de flux de donnees circulant entre les objets connectes. Dans cet article nous proposons d'adapter le BPM a la gestion des processus de l'IdO, pour ameliorer l'automatisation, l'ordonnancement et l'optimisation des donnees qui circulent entre les objets et\ou dans le Cloud en proposant un nouveau operateur semantique qu'on designe par « GIOT : Gateway for internet of things » pour favoriser un transfert intelligent de donnees en prenant comme cas d'etude une maison intelligente.

It has been shown that the maximum distance routing strategy which works well on a Unit Disk Graph (UDG), performs poorly when it is executed on a Non Unit Disk Graph (N-UDG) which reflects the radio irregularity phenomenon. This latter arises from multiple factors, such as antenna and medium type, and is accentuated by environmental factors such as obstacles (e.g., buildings, hills, mountains) and weather conditions. In this paper, we propose a Cross-Layer Greedy Routing algorithm (CL-GR) which enables a correct position-based routing on a N-UDG. It provides two novel greedy routing strategies, termed respectively, Progress towards the sink node through Symmetrical links that experience the lowest Path Loss (PSPL) and progress through symmetrical links, combining the Maximum Distance forwarding strategy and the PSPL (MDPSPL). We compare our CL-GR to an Enhanced version of the Greedy algorithm of the Greedy Perimeter Stateless Routing protocol (GPSR), that we call E-GR and which can be executed on a N-UDG, and to COP _ GARE algorithm. The simulation results show that both PSPL and MDPSPL enable higher Packet Delivery Ratio (PDR) and energy efficiency. In terms of end-to-end delay, while the PSPL strategy significantly increases this metric, the MDPSPL strategy enables a satisfactory end-to-end delay, comparatively to E-GR and COP _ GARE.

The main concern of clustering approaches for mobile wireless sensor networks (WSNs) is to prolong the battery life of the individual sensors and the network lifetime. For a successful clustering approach the need of a powerful mechanism to safely elect a cluster head remains a challenging task in many research works that take into account the mobility of the network. The approach based on the computing of the weight of each node in the network is one of the proposed techniques to deal with this problem. In this paper, we propose an energy efficient and safe weighted clustering algorithm (ES-WCA) for mobile WSNs using a combination of five metrics. Among these metrics lies the behavioral level metric which promotes a safe choice of a cluster head in the sense where this last one will never be a malicious node. Moreover, the highlight of our work is summarized in a comprehensive strategy for monitoring the network, in order to detect and remove the malicious nodes. We use simulation study to demonstrate the performance of the proposed algorithm.

Outlier detection is the process of identifying the data objects that do not comply with the normal behavior of the defined data model. Used in automated data analysis, it ensures the desired data quality and reliability. This field has attracted increasing attention in the wireless sensor network domain, using methods from machine learning, data mining, and statistics. In this paper, we propose a novel outlier detection approach based on Copula theory. This powerful theory allows to model the dependency between data measurements in a formal and statistical way. We have evaluated our proposed approach with a real world dataset. Our results show a detection rate of 85.90% and an error rate of 0.87%.

Multi-path routing appears to be an essential feature for supporting the characteristics of wireless multimedia sensor networks. In fact, using multiple paths between the source and the destination can provide adequate network resources required by such networks. However, the effect of wireless interferences between paths severely affects the performance of this approach. In this paper, we propose a simple interference-aware multipath routing protocol and study the effects of inter-path interferences on the received video quality in the context of wireless multimedia sensor networks. We show, through simulations, that minimizing interferences between the transmission paths can provide necessary bandwidth to support multimedia applications when small frame rates are used.

International audience; Surveillance applications based on Wireless Sensor Networks (WSNs) are energy consumption sensitive. Such applications require low energy consumption in order to extend network lifetime. In this paper, we are interested in event detection around strategic sites (e.g., oil or military sites). We propose energy efficient approach which consists of identifying and using network boundary nodes as sentries, i.e., they are always in active mode and are responsible of detecting events, sending and relaying alert messages to the sink. Remaining nodes are used as relay nodes only. They alternate between active and sleep modes in order to reduce energy consumption. Simulation results show that our approach increases significantly network lifetime and provides an acceptable percentage of alert messages received by the sink.

Wireless video sensor networks (WVSNs) have recently emerged as a new class of sensor networks in which large amounts of visual data are sensed. This kind of networks, strengthened with rotation capability for each video sensor, is envisioned to be deployed to monitor a plethora of real-world phenomena. In this work, we propose a model of WVSN for post-disaster management in order to assist search and rescue operations by locating survivors and identifying risky areas. Rotatable video sensors are randomly deployed and used to switch to the best direction with the purpose of getting high coverage while avoiding obstacles. To address fault tolerance problem in WVSN, we build potential cover sets to unsure field of view's coverage of failed nodes. We have conducted a set of comprehensive experiments using OMNeT++ simulator and the obtained results reveal that our proposal gives better performance in terms of coverage enhancement and fault tolerance.

Wireless Video Sensor Networks (WVSNs) have become a leading solution in many important applications, such as disaster recovery. By using WVSNs in disaster scenarios, the main goal is achieving a successful immediate response including search, location, and rescue operations. The achievement of such an objective in the presence of obstacles and the risk of sensor damage being caused by disasters is a challenging task. In this paper, we propose a fault tolerance model of WVSN for efficient post-disaster management in order to assist rescue and preparedness operations. To get an overview of the monitored area, we used video sensors with a rotation capability that enables them to switch to the best direction for getting better multimedia coverage of the disaster area, while minimizing the effect of occlusions. By constructing different cover sets based on the field of view redundancy, we can provide a robust fault tolerance to the network. We demonstrate by simulating the benefits of our proposal in terms of reliability and high coverage.

Summary In this paper, the random access procedure of Universal Mobile Telecommunications System network is investigated. We have proposed a model based on communicating timed automata that represents the main functions related to the random access procedure including the user equipment, the base station (node B or BTS), and the channel. Then, we have used computational tree logic formula to specify the proprieties to be verified. The model and the formulas serve as inputs to the model checker, which is used as a verification engine, ie, UPPAAL and SPIN. The formal verification approach shows that the protocol has several drawbacks that may not be detected by simulation.

International audience; Wireless video sensor networks (WVSN) are foreseen to be a key driver of the development of pervasive applications of every-day life. They trigger very challenging problems due to their constrained nature in terms of energy, bandwidth, processing and storage means. In order to be able to assess the performances of their proposals, WVSN's researchers community needs a transmission and evaluation tool that considers WSN specific characteristics. In this paper, we propose EvalVSN, a new tool for video transmission and evaluation targeted to WVSN. EvalVSN allows both real and simulation-based video transmissionand evaluation in WSN. Currently application modules that make use of EvalVSN trace files are available in TinyOS, ns2 and Castalia environments.

Wireless Video Sensor Networks (WVSNs) have recently emerged as a new type of sensor networks in which large amounts of data are sensed and processed in real-time. This kind of networks is envisioned to be deployed in the physical environment to monitor a wide variety of real-world phenomena such as surveillance, monitoring and disaster recovery. In this work we propose a model of WVSN for post-disaster management in order to assist rescue operations by locating survivors, identifying risky areas and making the rescue crew more aware of the overall situation. To build an overview of the environment and to assess the current situation, we have used rotatable video sensors functionalities, which can switch to the best direction to get high coverage. After these video sensors are randomly deployed, each sensor calculates its next new direction to switch in order to obtain a better coverage than previous one. To address fault tolerance in WVSN in case of damages caused by disasters, we used redundant video nodes to construct different cover sets composed of video sensors that can cover the failed video node's Field of View. Simulation results show the effectiveness of our scheme in terms of coverage enhancement and fault tolerance.

The main role of wireless sensor networks (WSN) is to collect sensor environmental data from monitored area. Due to faults or malicious nodes, sensor data collected or reported might be wrong. Hence it is important to detect the presence of wrong sensor readings and misleading reports [18]. In this paper, we present a formal model using Time Petri Net to formally evaluate a proposed solution for detecting wormhole attack in CL-MAC, a cross-layer MAC protocol developed at MAC layer for energy efficient and low latency in WSN [3] [7]. Lunching wormhole attack in CL-MAC can cause the protocol invalid in some scenarios. Wormhole attack in CL-MAC is discussed, and a formal approach based on Time Petri Net (TPN) to detect wormhole attack is presented. TiNA (Time Net Analyzer) TPN tool is used to highlight the formal properties of the proposed solution. The obtained analytical results show that the secured version of CL-MAC can effectively detect and avoid wormhole attack, and make more sensor nodes perform a valid behavior.

Recent advances in miniature mobile robotics have fostered the emergence of mobile wireless sensor networks (MWSN). As sensor nodes are battery-powered devices, the first important constraint is how to reduce the energy consumption to extend the lifetime of the network. In this paper, we propose an optimisation approach based on integer linear programming (0-1 ILP) to significantly reduce energy consumption in MWSN. To do so, we formulate the problem as an objective function aiming to minimise the overall energy consumption related to communication operations and the mobility of the sensor nodes and/or sink. The developed formulation is performed under some realistic and relevant constraints of MWSN, such as sensing coverage, connectivity, adjustable transmission range and the case of adjustable sensing range. The proposed approach is evaluated using flat and cluster-based topologies by doing intensive experiments using the CPLEX solver. The obtained results reveal that the mobility factor in MWSN coupled with the considered additional constraints makes it possible to extend significantly the network lifetime.

Video monitoring for infrastructure surveillance and control is a special case of wireless sensor network applications in which large amounts of data are sensed and processed in real-time, and then communicated over a wireless network called a Wireless Video Sensor Network (WVSN). Effectively managing of such as networks is a major challenge. Considering that, a critical issue is the quality of the deployment from the sensing coverage viewpoint. Area coverage is still an essential issue in a WVSN. In this paper, we study the area coverage problem in WVSN with rotatable sensors, which can switch to the best direction to get high coverage. After the video sensors are randomly deployed, each sensor calculates its next new direction to switch in order to obtain a better coverage than previous one. In order to extend the network lifetime, our approach is to define a subset of the deployed nodes called a cover set to be active while the other nodes can sleep. Our proposed scheme is implemented and tested in OMNeT++ and shows significant enhancement in terms of average percentage of coverage.

CL-MAC: Cross-layer MAC Protocol for Delay Sensitive Wireless Sensor Network Applications

Technological Advances in microelectronic and telecommunication fields enable the existence of tiny computing units, very small and more efficient. In the context of these new technologies, Wireless Sensor Networks (WSN) have emerged. The main research objective in WSN domain is the development of algorithms and protocols ensuring minimal energy consumption. Most proposed solutions are based on one-layer stack model approach. Recently, other works tend to exploit together many layers in order to optimize energy consumption. In this paper, we propose a Cross-Layer Medium Access Control (CL-MAC) protocol using two adjacent layers (MAC and Network) to economize energy for WSN. The basic idea behind our protocol is to wake-up only nodes belonging to a routing path from the source to the base station (Sink) by exploiting routing information while other nodes leave maintained as long time as possible in a sleep mode. The protocol is modeled using a time Petri net and validated by TiNA tool. The simulation results demonstrate the effectiveness of our proposal in terms of energy consumption and latency.

Most of Wireless Sensor Networks (WSNs) routing solutions use mainly static sinks to collect data from the entire network. This collection approach results in high traffic load in the sink's vicinity because neighborhood nodes of the sink will be more requested than others nodes in the network. Therefore, these nodes will consume more energy and face high congestion in a large scale WSN. To mitigate this problem, two approaches of mobile networks, according to the type of the mobile element, are today considered as a possible solution to minimize the energy consumption: mobile Sink and mobile relay nodes [1]. Our aim in this paper is to studythe impact of the mobile element (Sink and relay nodes) on WSN performancesin terms of energy efficiency, number of received messages as well as latency by using a simulation approach.The obtained results have revealed that the collection approach based on relay nodes give better performance than those based on mobile Sink.