Multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks
02 May 2018-Eurasip Journal on Wireless Communications and Networking (SpringerOpen)-Vol. 2018, Iss: 1, pp 1-11
TL;DR: This paper proposes multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks (MAEF) to plan itineraries for MAs by grouping nodes in clusters and planning itineraries efficiently among cluster heads (CHs) only.
Abstract: Mobile agent (MA)-based wireless sensor networks present a good alternative to the traditional client/server paradigm. Instead of sending the data gathered by each node to the sink as in client/server, MAs migrate to the sensor nodes (SNs) to collect data, thus reducing energy consumption and bandwidth usage. For MAs, to migrate among SNs, an itinerary should be planned before the migration. Many approaches have been proposed to solve the problem of itinerary planning for MAs, but all of these approaches are based on the assumption that MAs visit all SNs. This assumption, however, is inefficient because of the increasing size of the MAs after visiting each node. Also, in case of node(s) failure, as it is often the case in WSNs, the MAs may not be able to migrate among SNs. None of the proposed approaches takes into consideration the problem of fault tolerance. In this paper, we propose multi-mobile agent itinerary planning-based energy and fault aware data aggregation in wireless sensor networks (MAEF) to plan itineraries for MAs. This can be achieved by grouping nodes in clusters and planning itineraries efficiently among cluster heads (CHs) only. What is more, an alternative itinerary is planned in case of node(s) failure. The simulation result clearly shows that our novel approach performs better than the existing ones.
Citations
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TL;DR: MCTM uses mobile code to visit the SN s based on pre-defined itineraries while collecting necessary details about these SN s in preparation for assessing their trust, demonstrating a superior performance over a state-of-art technique that is energy-efficient management based on Software-Defined Network ( SDN ) for SN s.
50 citations
TL;DR: A Mobile-Agent Distributed Intelligence Tangle-Based approach (MADIT) is proposed as a potential solution based on IOTA (Tangle), where Tangle is a distributed ledger platform that enables scalable, transaction-based data exchange in large P2P networks.
Abstract: It is estimated that there will be approximately 125 billion Internet of Things (IoT) devices connected to the Internet by 2030, which are expected to generate large amounts of data. This will challenge data processing capability, infrastructure scalability, and privacy. Several studies have demonstrated the benefits of using distributed intelligence (DI) to overcome these challenges. We propose a Mobile-Agent Distributed Intelligence Tangle-Based approach (MADIT) as a potential solution based on IOTA (Tangle), where Tangle is a distributed ledger platform that enables scalable, transaction-based data exchange in large P2P networks. MADIT enables distributed intelligence at two levels. First, multiple mobile agents are employed to cater for node level communications and collect transactions data at a low level. Second, high level intelligence uses a Tangle based architecture to handle transactions. The Proof-of-Work offloading computation mechanism improves efficiency and speed of processing, while reducing energy consumption. Extensive experiments show that transaction processing speed is improved by using mobile agents, thereby providing better scalability.
26 citations
TL;DR: This paper implements, simulate and compare the most prominent itinerary planning algorithms upon a common parameter space, making realistic network-level assumptions.
Abstract: In wireless sensor networks (WSNs), mobile agent (MA) is a new paradigm that has gained more attention lately. In this paradigm, MA migrates among sensor nodes (SNs) for data fusion. However, in comparison to traditional client/server paradigm; where each SN in the network sends its collected data to the sink, MA presents a good alternative in terms of energy consumption, response time and network lifetime. In this paradigm, the most critical properties of MA is the itinerary planning, it has always been an issue and a NP-hard problem. In this paper, we present a survey of the proposed itinerary planning approaches for MAs in WSNs. MA itinerary planning techniques can be classified into three categories: static itinerary planning, dynamic itinerary planning and hybrid itinerary planing. The benefits and shortcomings of different MA itinerary planning approaches are presented. Furthermore, we implement, simulate and compare the most prominent itinerary planning algorithms upon a common parameter space, making realistic network-level assumptions.
15 citations
TL;DR: An Energy Aware Decision Stump Linear Programming Boosting Node Classification based Data Aggregation (EADSLPBNC-DA) Model is proposed and significantly reduces the energy consumption, delay, data aggregation accuracy, network lifetime and data aggregation time when compared to the existing techniques.
10 citations
TL;DR: An energy-efficient privacy-preserving data aggregation protocol based on slicing (EPPA) where a novel slicing mode is adopted to reduce the numbers of slices is presented, which can significantly prevent the data from being compromised and decrease the communication overhead.
Abstract: Wireless sensor networks (WSNs) have become one of the most vigorous techniques in the network domain. However, the sensor nodes of WSNs tend to become the target of attackers due to the broadcast communication mode and the unattended deployment nature. Although it can prevent the sensitive data from being compromised, Slice-Mix-AggRegaTe (SMART) needs to exchange messages frequently in a network, which put tremendous overhead on the sensor nodes with limited resources. Faced with these issues, this paper proposes an energy-efficient privacy-preserving data aggregation protocol based on slicing (EPPA) where a novel slicing mode is adopted to reduce the numbers of slices, which can significantly prevent the data from being compromised and decrease the communication overhead. Meanwhile, an enhanced scheme based on EPPA, called multi-function privacy-preserving data aggregation protocol (MPPA), is presented and it supports multiple functions in the process of data aggregation, such as max/min, count, and mean. The theoretical analysis and the simulation evaluation show that the proposed aggregation protocols demonstrate a better performance in the privacy preserving and the communication efficiency.
9 citations
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"Multi-mobile agent itinerary planni..." refers background in this paper
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