Biologically inspired node scheduling control for wireless sensor networks

Byun, Heejung; Son, Sugook; Yang, Soomi

doi:10.1109/jcn.2015.000089

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…In all conducted simulation results, the HWOA show substantially better performance than traditional Whale Optimization Algorithm (WOA) approaches in terms of resource scheduling delay with efficient load balancing [28]. The convergence of bio-computing and scheduling algorithms for WSN is discussed in [29,30].…”

Section: Literature Surveymentioning

confidence: 97%

Agent driven resource scheduling in wireless sensor networks: fuzzy approach

Kori¹,

Kakkasageri²

2021

Int. j. inf. tecnol.

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Wireless sensor network (WSN) provides a significant contribution in emerging fields such as ubiquitous computing, ambient intelligence, Internet of Things, etc. WSN is a highly distributed computing network of tiny sensors which are self-conscious and are deployed in different geographical area randomly for multiple applications. These tiny sensor motes are insecure about resources such as bandwidth, battery, and communication range, etc. To increase the life span of WSN, effective utilization of available network resources is very important. Consequently, WSN's efficient and productive resource management is a challenging task involving the identification of resources, scheduling of resources, allocation of resources. In this paper, a type-2 fuzzy logic system (T2FLS) based resource scheduling technique using a software agent approach to resolve the scheduling issues by considering energy, number of neighboring nodes, and available bandwidth of WSN is proposed. Proposed software agent based resource scheduling scheme comprises of node agency (NA) and sink agency (SA). Both agencies comprised of a mobile agent and static agent. SA periodically gathers information related to a node such as available energy, bandwidth, and degree of connectivity collected by NA. Based on these parameters SA makes the suitable resource scheduling decision. Simulation results show that the performance of the proposed type-2 fuzzy with agent based approach is better as compared with the trusted real time scheduling model for wireless sensor networks (TRTSM) scheme in terms of scheduling accuracy, scheduling delay, and bandwidth utilized.

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Section: Literature Surveymentioning

confidence: 97%

Agent driven resource scheduling in wireless sensor networks: fuzzy approach

Kori¹,

Kakkasageri²

2021

Int. j. inf. tecnol.

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“…DoF of the circular multirelay MIMO interference channel is analyzed, while full duplex MIMO is deployed in [24]. To reduce the intercell interference and limit the energy consumption, power is allocated due to the scheduling scheme [20], [25]- [27]. Codebook is utilized to limit the system computing complexity [28].…”

Section: B Radio Resource Managementmentioning

confidence: 99%

A Joint Scheduling and Beamforming Scheme for RoF-Aided MC-SSN

Chen

Zhang

2019

IEEE Access

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Applied to harsh scenarios, the mission critical sensors and sensor network (MC-SSN) is expected to be of high capacity, density, and low cost. Both the industry and research community have a consensus on the need for energy and spectrum saving. Radio over fiber (RoF) system is promising for low latency and flexible system of high efficiency. In this paper, we consider the RoF-aided MC-SSN system serving the sensors with massive multiple-input multiple-output (MIMO) equipped. Based on this model, the base stations, relays, and other network elements can set up connections with each other via optical fiber or wireless links. Aiming to maximize the energy efficiency, this paper proposes a scheme including two aspects: 1) scheduling of the sensors based on the direction of arrival sensing of interference an 2) massive MIMO beamforming matrices generation based on a codebook. The numerical results show that the proposed scheduling and resource allocation method can achieve sufficient throughput with reduced power consumption for the RoF-aided MC-SSN system.

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“…Routing [20], clustering, and energy harvesting [21], self-synchronization techniques [22], security [23] (1) We first discuss and formulate the optimal PCID configuration problem in 5G UDN. Subsequently, we prove that the global optimal solution is computationally complex and NP-complete.…”

Section: Wsnmentioning

confidence: 99%

“…Similarly, ant-colony based optimization [16], bee-colony based optimization [19], and genetic algorithms [28] are the major 4 Wireless Communications and Mobile Computing bioinspired tools used for learning troubleshooting fuzzy rules and optimization in self-healing wireless networks. On the other hand, wireless sensors networks use bioinspired solution for optimal clustering [21], routing path selection, and energy efficient coverage scheduling [20]. Reference [14] provides an overview of researchers working on solutions related to bioinspired networking along with practical relevance and capabilities of bioinspired networking.…”

Section: Wsnmentioning

confidence: 99%

BiSON: A Bioinspired Self‐Organizing Network for Dynamic Auto‐Configuration in 5G Wireless

Roy¹,

Saxena

Sahu

et al. 2018

Wireless Communications and Mobile Computing

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Emerging 5G wireless networks are expected to herald significant transformation in industrial applications, with improved coverage, high data rates, and massive device capacity. However, the introduction of 5G wireless makes the network configuration, management, and planning extremely challenging. For efficient network configuration, every cell needs to be allocated a particular Physical Cell Identifier (PCID), which is unique in its vicinity. Wireless standards (e.g., 3GPP) typically specify a limited number of PCIDs. However, the number of cells in 5G Ultradense Networks (UDN) is expected to significantly outnumber these limited PCIDs. Hence, these PCIDs need to be efficiently allocated among the myriad of cells, such that two cells which are neighbors or neighbor’s neighbor are assigned with different PCIDs. This complicated network configuration problem becomes even more complex by dynamic introduction and removal of 5G small cells (e.g., micro, femto, and pico). In this paper, we introduce BiSON, a new Bioinspired Self-Organizing Solution for automated and efficient PCID configuration in 5G UDN. Using two different extensions, namely, “always near-optimal” and “heuristic,” we explain near-optimal and dynamic auto-configuration in computationally feasible time, with negligible overhead. Our extensive network simulation experiments, based on actual 5G wireless trials, demonstrate that the proposed algorithm achieves better optimality (minimum PCIDs in use) than earlier works in a reasonable computational complexity.

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Biologically inspired node scheduling control for wireless sensor networks

Cited by 8 publications

References 28 publications

Agent driven resource scheduling in wireless sensor networks: fuzzy approach

Agent driven resource scheduling in wireless sensor networks: fuzzy approach

A Joint Scheduling and Beamforming Scheme for RoF-Aided MC-SSN

BiSON: A Bioinspired Self‐Organizing Network for Dynamic Auto‐Configuration in 5G Wireless

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