Energy efficient clustering scheme with secure data aggregation for mobile Wireless Sensor Networks (EECSSDA)

Mohan, B. A.; Dayananda, Karanam Ravichandran; H, Saroja Devi

doi:10.1109/get.2016.7916636

Cited by 9 publications

(6 citation statements)

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“…In second phase, every node chooses its CH which has higher potential score. All cluster members will transmit the data to cluster heads for aggregation and encryption, which is then forwarded to the base station [12]. Ledan Cheng, et al [2016] our propose a novel energy-efficient dynamic clustering algorithm by utilizing spatial correlation, which can achieve a distributed compressive data aggregation in each CH.…”

Section: Literature Surveymentioning

confidence: 99%

Enhanced Technique for Selection of Cluster Head in Wireless Sensor Network

2017

IJAERD

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Section: Literature Surveymentioning

confidence: 99%

Enhanced Technique for Selection of Cluster Head in Wireless Sensor Network

2017

IJAERD

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“…In this section, simulation results are presented for the proposed NESRA algorithm, compared to the existing baseline algorithms. For existing algorithms, EECSSDA [62] and LEACH-M [41] are selected. EECSSDA performs security resource allocation based on the mobility and remaining energy of the nodes in the network.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Some CHs may be present at the side of the cluster. In the next sections, the performance of the proposed NESRA algorithm is discussed and compared with some existing algorithms, EECSSDA [62] and LEACH-M [41]. .5(a) shows the average total percentage of energy spent for all cycles in the network.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Thus, the overall complexity has a quadratic relation with the total number of sensor nodes and a linear relation with the number of clusters. This is competitive with other algorithms such as NESRA [11], EECSSDA [62], and LEACH-M [45].…”

Section: Complexity Analysismentioning

confidence: 90%

“…However, the security in the aforementioned works is not evaluated. In [62], an Energy Efficient Clustering Scheme with Secure Data Aggregation (EECSSDA) is proposed for mobile networks. EECSSDA selects CHs based on the potential score value, which is a weighted function of mobility, neighboring sensor nodes' density, and sensor nodes' residual energy percentage, which is directly related to the security resources available at sensor nodes.…”

Section: Security-aware Algorithmsmentioning

confidence: 99%

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Cluster-Based Information-Centric Wireless Sensor Networks Management for Enhanced User Security Satisfaction in the Internet of Things

Gharib¹

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Many Internet of Things applications, such as smart cities and intelligent transportation, require accessible data to users (i.e., data consumers). To address users' timely data access needs, Information-Centric Wireless Sensor Networks (ICWSNs) were proposed that allow users to access data directly from cache nodes. Particularly, ICWSNs are clustered, and Cluster Heads (CHs) are selected to collect data from basic sensing nodes and act as cache nodes. Nevertheless, clustering and ensuring data security in ICWSNs is challenging. This is because sensor nodes are often resource-constrained, heterogeneous (i.e., perform different sensing tasks), and/or mobile.Driven by users' security and timely data access needs, in this thesis, cluster-based ICWSNs' management for enhanced user security satisfaction is investigated. First, a security-aware CHs selection algorithm is proposed to optimize network coverage that is subject to security and energy constraints. Then, cluster-based ICWSNs with heterogeneous communities are modeled analytically and compared to conventional cluster-based ICWSNs with heterogeneous sensor nodes. To overcome the identified energy-latency and security trade-off, a Security Level Aware algorithm for Clusterbased ICWSNs with Heterogeneous communities (SLAC-H) is proposed. In SLAC-H, community leaders collect and forward application-domain-specific data to CHs. Next, Node Embedding with Security Resource Allocation (NESRA) clustering algorithm for mobile ICWSNs is proposed. To improve user security satisfaction, NESRA allocates security resources to sensor nodes based on their location, mobility, and energy resources. Still, when security is set as a priority, many times, more energy is spent on security than is actually required. Therefore, along with the mobility-aware NESRA, User-aware clustering with Security Resource Allocation (USRA) algorithm is proposed. In USRA, a sink node determines which security resource each sensor node will be using for the next round to avoid over-utilization of network resources while satisfying user security needs. A summary of the proposed algorithms and some highlights for future work conclude this thesis. List of Publications List of References viii List of Tables 4.1 Security levels mapping based on the security mechanism used [65]. .

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Energy-Efficient Hybrid Protocol for Routing Based on Mobile Data Collectors in Wireless Sensor Network

Mohan

Sarojadevi

2017

Smart Computing and Informatics

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Energy efficient clustering scheme with secure data aggregation for mobile Wireless Sensor Networks (EECSSDA)

Cited by 9 publications

References 10 publications

Enhanced Technique for Selection of Cluster Head in Wireless Sensor Network

Enhanced Technique for Selection of Cluster Head in Wireless Sensor Network

Cluster-Based Information-Centric Wireless Sensor Networks Management for Enhanced User Security Satisfaction in the Internet of Things

Energy-Efficient Hybrid Protocol for Routing Based on Mobile Data Collectors in Wireless Sensor Network

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