Ant-based delay-bounded and power-efficient data aggregation in wireless sensor networks

2019 ◽  
Vol 15 (2) ◽  
pp. 97-119
Author(s):  
Nadjib Benaouda ◽  
Ammar Lahlouhi
Keyword(s):  
Data Aggregation ◽  
Sensor Nodes ◽  
Network Data ◽  
Transmission Power ◽  
Power Assignment ◽  
Content Type ◽  
Power Efficient ◽  
Total Transmission ◽  
Efficient Data ◽  
Energy Latency

Purpose The purpose of this paper is to present a novel delay-bounded and power-efficient routing for in-network data aggregation, called DPIDA, which aims to ensure a compromise between the energy consumed during the collection of data sensed by a set of source sensor nodes and their timely delivery to the sink node. Design/methodology/approach Based on the ant-colony-optimization metaheuristic, the proposal establishes a routing structure that maximizes the number of overlapping routes and minimizes the total transmission power while ensuring delay-bounded paths and a symmetric transmission power assignment to reliably deliver the sensed data. Findings The proposal was extensively compared to two other known protocols regarding different keys factors. Simulation results, including topology snapshots, show the ability of DPIDA to ensure the energy–latency tradeoff. They also show the superiority of DPIDA compared to the two considered protocols. Originality/value This paper presents a novel ant-based protocol that uses in-network data aggregation and transmission power-adjustment techniques to conserve the energy of nodes while ensuring delay-bounded paths and a reliable deliverance of data which is ensured by providing a symmetric transmission power assignment.

Detecting Wormhole Attack on Data Aggregation in Hierarchical WSN

2017 ◽  
Vol 11 (1) ◽  
pp. 35-51 ◽  
Author(s):  
Mukesh Kumar ◽  
Kamlesh Dutta
Keyword(s):  
Energy Efficiency ◽  
Data Aggregation ◽  
Low Cost ◽  
Attack Detection ◽  
Sensor Nodes ◽  
Network Data ◽  
Light Weight ◽  
Malicious Node ◽  
Combine Data ◽  
Wormhole Attack

Wireless networks are used by everyone for their convenience for transferring packets from one node to another without having a static infrastructure. In WSN, there are some nodes which are light weight, small in size, having low computation overhead, and low cost known as sensor nodes. In literature, there exists many secure data aggregation protocols available but they are not sufficient to detect the malicious node. The authors require a better security mechanism or a technique to secure the network. Data aggregation is an essential paradigm in WSN. The idea is to combine data coming from different source nodes in order to achieve energy efficiency. In this paper, the authors proposed a protocol for worm hole attack detection during data aggregation in WSN. Main focus is on wormhole attack detection and its countermeasures.

scholarly journals In-Network Data Processing in Software-Defined IoT with a Programmable Data Plane

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Ki-Wook Kim ◽  
Sung-Gi Min ◽  
Youn-Hee Han
Keyword(s):  
Data Processing ◽  
Data Aggregation ◽  
Sensor Nodes ◽  
Network Data ◽  
Packet Forwarding ◽  
Processing Scheme ◽  
Sensing Data ◽  
Iot Applications ◽  
Proposed Model ◽  
Data Plane

Making an SDN data plane flexible enough to satisfy the various requirements of heterogeneous IoT applications is very desirable in terms of software-defined IoT (SD-IoT) networking. Network devices with a programmable data plane provide an ability to dynamically add new packet- and data-processing procedures to IoT applications. The previously proposed solutions for the addition of the programmability feature to the SDN data plane provide extensibility for the packet-forwarding operations of new protocols, but IoT applications need a more flexible programmability for in-network data-processing operations (e.g., the sensing-data aggregation from thousands of sensor nodes). Moreover, some IoT models such as OMG DDS, oneM2M, and Eclipse SCADA use the publish-subscribe model that is difficult to represent using the operations of the existing message-centric data-plane models. We introduce a new in-network data-processing scheme for the SD-IoT data plane that defines an event-driven data-processing model that can express a variety of in-network data-processing cases in the SD-IoT environment. Also, the proposed model comprises a language for the programming of the data-processing procedures, while a flexible data-plane structure that can install and execute the programs at runtime is additionally presented. We demonstrate the flexibility of the proposed scheme by using sample programs in a number of example SD-IoT cases.

scholarly journals Transmission Power Control with the Guaranteed Communication Reliability in WSN

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Dae-Young Kim ◽  
Zilong Jin ◽  
Jungwook Choi ◽  
Ben Lee ◽  
Jinsung Cho
Keyword(s):  
Wireless Sensor Network ◽  
Power Control ◽  
Sensor Network ◽  
Data Transmission ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Transmission Power ◽  
Efficient Data ◽  
Communication Reliability

In a wireless sensor network, sensor nodes are deployed in an ad hoc fashion and they deliver data packets using multihop transmission. However, transmission failures occur frequently in the multihop transmission over wireless media. Thus, a loss recovery mechanism is required to provide end-to-end reliability. In addition, because the sensor nodes are very small devices and have insufficient resources, energy-efficient data transmission is crucial for prolonging the lifetime of a wireless sensor network. This paper proposes a transmission power control mechanism for reliable data transmission, which satisfies communication reliability through recovery of lost packets. The proposed method calculates packet reception rate (PRR) of each hop to maintain end-to-end packet delivery rate (PDR), which is determined based on the desired communication reliability. Then, the transmission power is adjusted based on the PRR to reduce energy consumption. The proposed method was evaluated through extensive simulations, and the results show that it leads to more energy-efficient data transmission compared to existing methods.

Energy-Efficient Data-Aggregation Technique for Correlated Spatial and Temporal Data in Cluster-Based Sensor Networks

2020 ◽  
Vol 16 (2) ◽  
pp. 53-68
Author(s):  
Khushboo Jain ◽  
Anoop Kumar
Keyword(s):  
Sensor Networks ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Data Gathering ◽  
Base Station ◽  
Sensor Nodes ◽  
Temporal Data ◽  
Network Applications ◽  
Efficient Data ◽  
Aggregation Technique

Continuous-monitoring applications in sensor network applications require periodic data transmissions to the base-station (BS), which may lead to unnecessary energy depletion. The energy-efficient data aggregation solutions in sensor networks have evolved as one of the favorable fields for such applications. Former research works have recommended many spatial-temporal designs and prototypes for successfully minimizing the data-gathering overheads, but these are constrained to their relevance. This work has proposed a data aggregation technique for homogeneous application set-ups in sensor networks. For this, the authors have employed two ways of model generation for reducing correlated spatial-temporal data in cluster-based sensor networks: one at the Sensor nodes (SNs) and the other at the Cluster heads (CHs). Building on this idea, the authors propose two types of data filtration, first at the SNs for determining temporal redundancies (TRs) in data readings by both relative deviation (RD) and adaptive frame method (AFM) and second at the CHs for determining spatial redundancies (SRs) by both RD and AFM.

High throughput SRAM design for improved computing in autonomous systems

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kumar Neeraj ◽  
Jitendra Kumar Das
Keyword(s):  
High Throughput ◽  
High Speed ◽  
Soft Errors ◽  
Autonomous Systems ◽  
Sensor Nodes ◽  
Short Supply ◽  
Content Type ◽  
Power Efficient ◽  
Sram Design ◽  
Level Shifter

PurposeHigh throughput and power efficient computing devices are highly essential in many autonomous system-based applications. Since the computational power keeps on increasing in recent years, it is necessary to develop energy efficient static RAM (SRAM) memories with high speed. Nowadays, Static Random-Access Memory cells are predominantly liable to soft errors due to the serious charge which is crucial to trouble a cell because of fewer noise margins, short supply voltages and lesser node capacitances.Design/methodology/approachPower efficient SRAM design is a major task for improving computing abilities of autonomous systems. In this research, instability is considered as a major issue present in the design of SRAM. Therefore, to eliminate soft errors and balance leakage instability problems, a signal noise margin (SNM) through the level shifter circuit is proposed.FindingsBias Temperature Instabilities (BTI) are considered as the primary technology for recently combined devices to reduce degradation. The proposed level shifter-based 6T SRAM achieves better results in terms of delay, power and SNM when compared with existing 6T devices and this 6T SRAM-BTI with 7 nm technology is also applicable for low power portable healthcare applications. In biomedical applications, Body Area Networks (BANs) require the power-efficient SRAM design to extend the battery life of BAN sensor nodes.Originality/valueThe proposed method focuses on high speed and power efficient SRAM design for smart ubiquitous sensors. The effect of BTI is almost eliminated in the proposed design.

scholarly journals Location-based key management, data authentication and aggregation in wireless sensor networks

2021 ◽  
Author(s):  
Jie Xiao
Keyword(s):  
Data Aggregation ◽  
Key Management ◽  
Base Station ◽  
Sensor Nodes ◽  
Message Authentication ◽  
Authentication Code ◽  
Data Authentication ◽  
Efficient Data ◽  
Group A ◽  
Previous Design

The first design presents a novel location-based key management and en-route data authentication proposal. It divides the whole sensing area into a number of location cells. A group of location cells consist of a logical group. A pairwise key between two sensor nodes is established based on grid-based bivariate t-degree polynomials. Any valid reading report needs to collect enough message authentication code (MACs) from different neighbours. These pairwise keys used for generating the MAC are forwarded several hops down to the base station for future en-route data authentication. The second design proposes a greedy location-based secure and energy-efficient data aggregation approach. It further utilizes data aggregation based on the previous design by setting up control groups, applying pattern codes, selecting and switching control head nodes dynamically and periodically. In addition, different from the first design, it only requires control head nodes to collect enough MACs in each reading report. Extensive analysis, evaluations and experiments show us that both designs are secure, efficient and resilient.

scholarly journals Computing Localized Power-Efficient Data Aggregation Trees for Sensor Networks

2011 ◽  
Vol 22 (3) ◽  
pp. 489-500 ◽  
Author(s):  
Huseyin Ozgür Tan ◽  
I Korpeoglu ◽  
Ivan Stojmenovic
Keyword(s):  
Sensor Networks ◽  
Data Aggregation ◽  
Power Efficient ◽  
Efficient Data

scholarly journals IoT Based Energy-Efficient Data Aggregation Wireless Sensor Network in Agriculture: A Review

2021 ◽  
Vol 58 (1) ◽  
pp. 2985-3007
Author(s):  
Vijay Nandal, Dr. Sunita Dahiya
Keyword(s):  
Data Aggregation ◽  
Power Dissipation ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Redundant Data ◽  
Battery Power ◽  
Efficient Data ◽  
Limited Power ◽  
The Internet Of Things

Sensor nodes generate Wireless Sensor Networks (WSNs), these networks have considerable application in the areas of habitat safety, disaster management, surveillance in defense, security & many more areas. WSNs are compact in size, with short battery power & additionally their processing capabilities are low. This restriction of battery power makes them vulnerably faulty. In order to save this limited power, redundant data must be stored inside the sensor node during aggregation which will result in a reduction power dissipation associated with the sending of unnecessary data. By aggregating data, we can control energy consumption by reducing redundancy.  Data aggregation is a really effective technique for WSN. In this paper we discuss the aggregation of data and their complex energy-efficient approach used for data aggregation in WSN. This paper highlights the latest innovations in WSNs vital for the research in agricultural domain, further we present their classification & did a comparative analysis of the discussed protocols, the nomenclature of energy saving & harvesting strategies used in agricultural monitoring. Further it discuss the difficulties and drawbacks of WSNs in context of agriculture, The presented comparative study will helpful in increasing number of data processing opportunities available through the Internet of Things (IoT).

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