Application of Soft Computing Techniques Over Hard Computing Techniques: A Survey

Chakraborty, Santanu; Sharma, Ramesh Kumar; Tewari, Pushpa

doi:10.18510/ijsrtm.2017.542

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…These soft-computing techniques are built upon two main principles: adaptivity (adaptation to new contexts) and knowledge (ability to learn). It should be noted that soft-computing techniques can be applied to hard-computing techniques to couple the advantages of these two approaches [ 88 ], that is, accuracy, quick decision making, low computational overheads, and low costs.…”

Section: Taxonomymentioning

confidence: 99%

Multi-Connectivity for 5G Networks and Beyond: A Survey

Sylla

Mendiboure

Maaloul

et al. 2022

Sensors

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To manage a growing number of users and an ever-increasing demand for bandwidth, future 5th Generation (5G) cellular networks will combine different radio access technologies (cellular, satellite, and WiFi, among others) and different types of equipment (pico-cells, femto-cells, small-cells, macro-cells, etc.). Multi-connectivity is an emerging paradigm aiming to leverage this heterogeneous architecture. To achieve this, multi-connectivity proposes to enable UE to simultaneously use component carriers from different and heterogeneous network nodes: base stations, WiFi access points, etc. This could offer many benefits in terms of quality of service, energy efficiency, fairness, mobility, and spectrum and interference management. Therefore, this survey aims to present an overview of multi-connectivity in 5G networks and beyond. To do so, a comprehensive review of existing standards and enabling technologies is proposed. Then, a taxonomy is defined to classify the different elements characterizing multi-connectivity in 5G and future networks. Thereafter, existing research works using multi-connectivity to improve the quality of service, energy efficiency, fairness, mobility management, and spectrum and interference management are analyzed and compared. In addition, lessons common to these different contexts are presented. Finally, open challenges for multi-connectivity in 5G networks and beyond are discussed.

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Section: Taxonomymentioning

confidence: 99%

Multi-Connectivity for 5G Networks and Beyond: A Survey

Sylla

Mendiboure

Maaloul

et al. 2022

Sensors

View full text Add to dashboard Cite

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“…Unfortunately, such assumptions are not met in practical reallife systems in which imprecision and unavailability of exact prior knowledge is the norm rather than an exception. Soft computing, in strict contrast to hard computing, can work with imprecision, uncertainty, and incomplete information to achieve approximate "good enough" solutions to computationally hard problems at lower costs [12] [13]. For example, soft computing can use computational intelligence techniques to heuristically solve intractable Non-deterministic Polynomial-time (NP-)complete problems [14] to produce approximate "good enough" solutions.…”

Section: Introductionmentioning

confidence: 99%

Soft Computing Techniques for Dependable Cyber-Physical Systems

et al. 2019

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Cyber-Physical Systems (CPS) allow us to manipulate objects in the physical world by providing a communication bridge between computation and actuation elements. In the current scheme of things, this sought-after control is marred by limitations inherent in the underlying communication network(s) as well as by the uncertainty found in the physical world. These limitations hamper fine-grained control of elements that may be separated by large-scale distances. In this regard, soft computing is an emerging paradigm that can help to overcome the vulnerabilities, and unreliability of CPS by using techniques including fuzzy systems, neural network, evolutionary computation, probabilistic reasoning and rough sets. In this paper, we present a comprehensive contemporary review of soft computing techniques for CPS dependability modeling, analysis, and improvement. This paper provides an overview of CPS applications, explores the foundations of dependability engineering, and highlights the potential role of soft computing techniques for CPS dependability with various case studies, while identifying common pitfalls and future directions. In addition, this paper provides a comprehensive survey on the use of various soft computing techniques for making CPS dependable.

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Routing in Wireless Sensor Networks Using Soft Computing

Kushwah

Dubey

2018

Advances in Computer and Electrical Engineering

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Wireless sensor networks are the evolutionary self-organizing multi-node networks. Due to dynamic network conditions and stochastically varying network environments, routing in WSNs is critically affected and needs to be optimized. The routing strategies developed for WSNs must be efficient to make it an operationally self-configurable network. For this we need to resort to near shortest path evaluation. Therefore, some soft computing approaches that can calculate the near shortest path available in an affordable computing time are required. WSNs have a high computational environment with limited and precise transmission range, processing, and limited energy sources. The sever power constraints strongly affect the existence of active nodes and hence the network lifetime. So, here, the authors use the power of soft computing because the potential features of soft-computing (SC) approach highly address their adaptability and compatibility to overwhelm the complex challenges in WSNs.

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Application of Soft Computing Techniques Over Hard Computing Techniques: A Survey

Cited by 3 publications

References 17 publications

Multi-Connectivity for 5G Networks and Beyond: A Survey

Multi-Connectivity for 5G Networks and Beyond: A Survey

Soft Computing Techniques for Dependable Cyber-Physical Systems

Routing in Wireless Sensor Networks Using Soft Computing

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