“…The MEC technology can solve the complex computing problems of ARMA operational process. This further guarantees the network performance.Algorithm 1. Pseudo-code of the relay selection algorithm. 1: if S = 1 then 2: S transmits messages via Relay 3: for t = 1 to 1000 do 4: for i = 1 to n do 5: for j = 1 to m do 6: Record the historical energy information for i th node and type-j service application, E Ri,j , in the candidate relay set ℜ at time t ; 7: x i,j ← E Ri,j ; 8: Ψ ← x i,j ; 9: Upload to MEC server with Ψ ; 10: Running ARMA prediction model according to the proposed ARMA (2,1) model on MEC server; 11: L ← ARMA (2,1) at time t + 1; 12: U = sort (L); 13: Q = fliplr (U); 14: n * = Q (1); 15: n * is denoted as the best relay-assisted node for one service application. 16: else 17: S is unable to communicate with D.…”
Section: The Proposed Relay-assisted Schemementioning
confidence: 72%
“…The details of the relay-assisted selection scheme, named as Algorithm 1, are in the top left corner of this page according to the above description. The operation is running in MEC server to reduce node energy consumption.…”
Section: The Proposed Relay-assisted Schemementioning
confidence: 99%
“…As a kind of energy-limited network, lower energy consumption is critical for sensor nodes, and nodes are confined in terms of batteries for wireless sensor network (WSN). 1,2 That is because nodes cannot be recharged in the process of network operation. 3 To reduce energy consumption of network, many technologies are proposed to achieve this goal, such as relay technology, [4][5][6] power allocation technology, 7,8 etc.…”
For energy-limited networks with real-time constraints, long-distance transmission, complex calculations, and limited delay are problems to be faced in service applications. The cloud-based mobile edge computing framework is proposed in energy-limited networks to solve these problems. Under certain power and delay conditions, source node and destination node in adjacent cells, respectively, can select the appropriate relay node to complete the communication process. The mobile edge computing brings a novel idea for the application of auto-regressive and moving average model and further improves transmission efficiency and reduces transmission delay. Historical energy information of potential relay nodes can be predicted through auto-regressive and moving average model in edge computing server. Then, source node selects appropriate relay node by the proposed relay selection algorithm. Power objective function with signal-tonoise ratio that satisfies the limited delay is formulated to optimize the power allocation of nodes in terms of reducing energy consumption. The results show that our proposed relay selection algorithm under mobile edge computing architecture in energy-limited networks with real-time constraints could effectively improve the performance of networks on energy consumption and delay.
“…The MEC technology can solve the complex computing problems of ARMA operational process. This further guarantees the network performance.Algorithm 1. Pseudo-code of the relay selection algorithm. 1: if S = 1 then 2: S transmits messages via Relay 3: for t = 1 to 1000 do 4: for i = 1 to n do 5: for j = 1 to m do 6: Record the historical energy information for i th node and type-j service application, E Ri,j , in the candidate relay set ℜ at time t ; 7: x i,j ← E Ri,j ; 8: Ψ ← x i,j ; 9: Upload to MEC server with Ψ ; 10: Running ARMA prediction model according to the proposed ARMA (2,1) model on MEC server; 11: L ← ARMA (2,1) at time t + 1; 12: U = sort (L); 13: Q = fliplr (U); 14: n * = Q (1); 15: n * is denoted as the best relay-assisted node for one service application. 16: else 17: S is unable to communicate with D.…”
Section: The Proposed Relay-assisted Schemementioning
confidence: 72%
“…The details of the relay-assisted selection scheme, named as Algorithm 1, are in the top left corner of this page according to the above description. The operation is running in MEC server to reduce node energy consumption.…”
Section: The Proposed Relay-assisted Schemementioning
confidence: 99%
“…As a kind of energy-limited network, lower energy consumption is critical for sensor nodes, and nodes are confined in terms of batteries for wireless sensor network (WSN). 1,2 That is because nodes cannot be recharged in the process of network operation. 3 To reduce energy consumption of network, many technologies are proposed to achieve this goal, such as relay technology, [4][5][6] power allocation technology, 7,8 etc.…”
For energy-limited networks with real-time constraints, long-distance transmission, complex calculations, and limited delay are problems to be faced in service applications. The cloud-based mobile edge computing framework is proposed in energy-limited networks to solve these problems. Under certain power and delay conditions, source node and destination node in adjacent cells, respectively, can select the appropriate relay node to complete the communication process. The mobile edge computing brings a novel idea for the application of auto-regressive and moving average model and further improves transmission efficiency and reduces transmission delay. Historical energy information of potential relay nodes can be predicted through auto-regressive and moving average model in edge computing server. Then, source node selects appropriate relay node by the proposed relay selection algorithm. Power objective function with signal-tonoise ratio that satisfies the limited delay is formulated to optimize the power allocation of nodes in terms of reducing energy consumption. The results show that our proposed relay selection algorithm under mobile edge computing architecture in energy-limited networks with real-time constraints could effectively improve the performance of networks on energy consumption and delay.
“…The ECC and AES are coupled in a way that sets them apart from other encryption methods. With the rising trend of security, it is more important than ever to properly secure data and information [9].…”
Section: Fig 3: Secure Systems In Cloud Infrastructure[6]mentioning
Cloud computing facilities have become an increasing rise in demand for presenting computing sources. Various programs like monetary transactions, fitness care systems, video streaming, IoT programs want on-call for provisioning of cloud sources to guarantee timeliness and excessive availability. A shared culture for data interchange has evolved as a result of the fast progress of networking technology. The data security has become a difficult issue as a result of the vast volume of data that is exchanged via the internet. Thus there is a requirement for security to protect data that is transmitted across an insecure connection. In our proposed work, privacy, confidentiality, availability, integrity, and accountability that contribute to the security of information are ensured by cryptographic technique. This paper also describes an exhaustive study on the usage of hybrid algorithms i.e. the combination of Advanced Encryption Standards (AES) and Elliptical Curve Cryptography (ECC) to protect data leakage and protect the privacy of end-users and SHA256 algorithm to ensure data integrity. This type of hybrid encryption will help not only in concentrating software as well as physical attacks but also provide the model to deal with and prevent the application from these types of attacks; thus making the cloud application system more secure. The implemented web application can be used as a defence system for privacy and security in organizations as well as institutions where members of the organization can share the file or confidential data to other team members or colleagues without data leakage thus providing data privacy and security.
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