Miloud Bagaa

Data Aggregation Scheduling Algorithms in Wireless Sensor Networks: Solutions and Challenges

Energy limitation is the main concern of any wireless sensor network application. The communication between nodes is the greedy factor for the energy consumption. One important mechanism to reduce energy consumption is the in-network data aggregation. In-network data aggregation removes redundancy as well as unnecessary data forwarding, and hence cuts on the energy used in communications. Recently a new kind of applications are proposed which consider, in addition to energy efficiency, data latency and accuracy as important factors. Reducing data latency helps increasing the network throughput and early events detection. Before performing the aggregation process, each node should wait for a predefined time called WT (waiting time) to receive data from other nodes. Data latency (resp., accuracy) is decreased (resp., increased), if network nodes are well scheduled through optimal distribution of WT over the nodes. Many solutions have been proposed to schedule network nodes in order to make the data aggregation process more efficient. In this paper, we propose a taxonomy and classification of existing data aggregation scheduling solutions. We survey main solutions in the literature and illustrate their operations through examples. Furthermore, we discuss each solution and analyze it against performance criteria such as data latency and accuracy, energy consumption and collision avoidance. Finally, we shed some light on future research directions and open issues after deep analysis of existing solutions.

UAV-Based IoT Platform: A Crowd Surveillance Use Case

Unmanned aerial vehicles are gaining a lot of popularity among an ever growing community of amateurs as well as service providers. Emerging technologies, such as LTE 4G/5G networks and mobile edge computing, will widen the use case scenarios of UAVs. In this article, we discuss the potential of UAVs, equipped with IoT devices, in delivering IoT services from great heights. A high-level view of a UAV-based integrative IoT platform for the delivery of IoT services from large height, along with the overall system orchestrator, is presented in this article. As an envisioned use case of the platform, the article demonstrates how UAVs can be used for crowd surveillance based on face recognition. To evaluate the use case, we study the offloading of video data processing to a MEC node compared to the local processing of video data onboard UAVs. For this, we developed a testbed consisting of a local processing node and one MEC node. To perform face recognition, the Local Binary Pattern Histogram method from the Open Source Computer Vision is used. The obtained results demonstrate the efficiency of the MEC-based offloading approach in saving the scarce energy of UAVs, reducing the processing time of recognition, and promptly detecting suspicious persons.

Semi-structured and unstructured data aggregation scheduling in wireless sensor networks

This paper focuses on data aggregation scheduling problem in wireless sensor networks (WSNs), to minimize time latency. Prior works on this problem have adopted a structured approach, in which a tree-based structure is used as an input for the scheduling algorithm. As the scheduling performance mainly depends on the supplied aggregation tree, such an approach cannot guarantee optimal performance. To address this problem, we propose approaches based on Semi-structured Topology (DAS-ST) and Unstructured Topology (DAS-UT). The approaches are based on two key design features, which are: (1) simultaneous execution of aggregation tree construction and scheduling, and (2) parent selection criteria that maximize the choices of parents for each node and maximize time slot reuse. We prove that the latency of DAS-ST is upper-bounded by ([2π/arccos(1/1+ϵ)]+4)R+Δ-4, where R is the network radius, Δ is the maximum node degree, and 0.05 <; ϵ ≤ 1. Simulations results show that DAS-UT outperforms DAS-ST and four competitive state-of-the-art aggregation scheduling algorithms in terms of latency and network lifetime.

Synchronization Protocols and Implementation Issues in Wireless Sensor Networks: A Review

Time synchronization in wireless sensor networks (WSNs) is a topic that has been attracting the research community in the last decade. Most performance evaluations of the proposed solutions have been limited to theoretical analysis and simulation. They consequently ignored several practical aspects, e.g., packet handling jitters, clock drifting, packet loss, and mote limitations, which affect real implementation on sensor motes. Authors of some pragmatic solutions followed empirical approaches for the evaluation, where the proposed solutions have been implemented on real motes and evaluated in testbed experiments. This paper gives an insight on issues related to the implementation of synchronization protocols in WSN. The challenges related to WSN environment are presented; the importance of real implementation and testbed evaluation are motivated by some experiments we conducted. The most relevant implementations of the literature are then reviewed, discussed, and qualitatively compared. While there are several survey papers that present and compare the protocols from the conception perspectives, as well as others that deal with mathematical and signal processing issues of the estimators, a survey on practical aspects related to the implementation is missing. To our knowledge, this paper is the first one that takes into account the practical aspect of existing solutions.

Efficient data aggregation with in-network integrity control for WSN

Energy is a scarce resource in Wireless Sensor Networks (WSN). Some studies show that more than 70% of energy is consumed in data transmission in WSN. Since most of the time, the sensed information is redundant due to geographically collocated sensors, most of this energy can be saved through data aggregation. Furthermore, data aggregation improves bandwidth usage and reduces collisions due to interference. Unfortunately, while aggregation eliminates redundancy, it makes data integrity verification more complicated since the received data is unique. In this paper, we present a new protocol that provides control integrity for aggregation in wireless sensor networks. Our protocol is based on a two-hop verification mechanism of data integrity. Our solution is essentially different from existing solutions in that it does not require referring to the base station for verifying and detecting faulty aggregated readings, thus providing a totally distributed scheme to guarantee data integrity. We carried out numerical analysis and simulations using the TinyOS environment. Results show that the proposed protocol yields significant savings in energy consumption while preserving data integrity, and outperforms comparable solutions with respect to some important performance criteria.

Distributed Low-Latency Data Aggregation Scheduling in Wireless Sensor Networks

This article considers the data aggregation scheduling problem, where a collision-free schedule is determined in a distributed way to route the aggregated data from all the sensor nodes to the base station within the least time duration. The algorithm proposed in this article (Distributed algorithm for Integrated tree Construction and data Aggregation (DICA)) intertwines the tree formation and node scheduling to reduce the time latency. Furthermore, while forming the aggregation tree, DICA maximizes the available choices for parent selection at every node, where a parent may have the same, lower, or higher hop count to the base station. The correctness of the DICA is formally proven, and upper bounds for time and communication overhead are derived. Its performance is evaluated through simulation and compared with six delay-aware aggregation algorithms. The results show that DICA outperforms competing schemes. The article also presents a general hardware-in-the-loop framework (DAF) for validating data aggregation schemes on Wireless Sensor Networks (WSNs). The framework factors in practical issues such as clock synchronization and the sensor node hardware. DICA is implemented and validated using this framework on a test bed of sensor motes that runs TinyOS 2.x, and it is compared with a distributed protocol (DAS) that is also implemented using the proposed framework.

End-to-end Network Slicing for 5G Mobile Networks

The research and development (R&D) and the standardization of the 5th Generation (5G) mobile networking technologies are proceeding at a rapid pace all around the world. In this paper, we introduce the emerging concept of network slicing that is considered one of the most significant technology challenges for 5G mobile networking infrastructure, summarize our preliminary research efforts to enable end-to-end network slicing for 5G mobile networking, and finally discuss application use cases that should drive the designs of the infrastructure of network slicing.

On using bargaining game for Optimal Placement of SDN controllers

In this paper we address the problem of Software Defined Networking (SDN) controller placement in large networks. Indeed, to solve the scalability issue raised by the centralized architecture of SDN, multi-controllers deployment (or distributed controllers system) is envisioned. However, the number and the location of controllers in large networks remain an issue. In this context, several works have been proposed to find the optimal placement of SDN controllers. Most of them consider latency among SDN controllers and switches as the main metric. In this work, we go beyond the state of art by proposing a solution that considers at the same time three critical objectives for the optimal placement of controllers: (i) the latency and communication overhead between switches and controllers; (ii)the latency and communication overhead between controllers; (iii) the guarantee of load balancing between controllers. We then solve the system by using Bargaining Game in order to find a fair trade off between these objectives. Simulation results clearly demonstrate the effectiveness of the proposed solution in finding the optimal placement of controllers that enforces this trade-off.

REFIACC: Reliable, efficient, fair and interference-aware congestion control protocol for wireless sensor networks

Abstract The recent wireless sensor network applications are resource greedy in terms of throughput and network reliability. However, the wireless shared medium leads to links interferences in addition to wireless losses due to the harsh environment. The effect of these two points translates on differences in links bandwidth capacities, lack of reliability and throughput degradation. In this study, we tackle the problem of throughput maximization by proposing an efficient congestion control-based schedule algorithm, dubbed REFIACC (Reliable, Efficient, Fair and Interference-Aware Congestion Control) protocol. REFIACC prevents the interferences and ensures a high fairness of bandwidth utilization among sensor nodes by scheduling the communications. The congestion and the interference in inter and intra paths hot spots are mitigated through tacking into account the dissimilarity between links’ capacities at the scheduling process. Linear programming is used to reach optimum utilization efficiency of the maximum available bandwidth. REFIACC has been evaluated by simulation and compared with two pertinent works. The results show that the proposed solution outperforms the others in terms of throughput and reception ratio (more than 80%) and can scale for large networks.

On Using SDN in 5G: The Controller Placement Problem

To integrate Software Defined Networking (SDN) in the envisioned 5G system, a separation of the control and user data plane functions of the Evolved Packet Core (EPC) is required. This separation will impact mainly the functions available at the Serving GateWay (SGW) and Packet data GateWay (PGW) elements, and will result in two new entities; i.e. the S/PGW-C and S/PGW-U (PGW-C and PGW-U). The S/PGW-C integrates all the control plane functions (such as signaling and tunnel creation), while S/PGW-U contains only forwarding functions. The S/PGW-C will control the S/PGW-U in order to forward the UE traffic to the appropriate destinations by enforcing rules e.g., using the Openflow protocol. Usually, the S/PGW-C will run as a Virtual Network Function (VNF) running on a Virtual Machine or Container instantiated over a federated cloud. In this paper, we focus on the problem of the SGW-C placement, where a tradeoff is needed between reducing the SGW relocation frequency and balancing the traffic load among the underlying SGW-C VNFs. We formulate this problem using optimisation models, and a fair solution (i.e. Pareto optimal) is derived using Nash Bargaining game and the threat point.