Research Article

[Retracted] Secure and Energy-Efficient Computational Offloading Using LSTM in Mobile Edge Computing

Table 2

A survey of the related methods with remarks.

SLNo.AuthorTitleMethodRemarks

1Orsini et al. [21]CloudAware: a context-adaptive middleware for mobile edge and cloud computing applicationsCloudAware as a holistic approachComputation offloading

2Al-Khafajiy et al. [22]IoT-fog optimal workload via fog offloadingCollaborative edge offloading techniqueMisses the fog nodes
Not energy efficient

3Li et al. [23]Deep reinforcement learning-based computation offloading and resource allocation for MECDeep reinforcement learning strategyAchieves significant reduction on the sum cost

4Anas et al. [24]Autonomous workload balancing in cloud federation environments with different access restrictionsPerformance model based on queuing theoryProvides a solution for access probability and resource utilization at a given time

5Ma et al. [25]Cooperative service caching and workload scheduling in mobile edge computingFuzzy logic method: developed an iterative algorithm named ICESolves the edge computing workload scheduling problem

6Sonmez et al. [26]Fuzzy workload orchestration for edge computingFuzzy logic methodLow complexity and efficiency in handling uncertain nonlinear systems

7Santoro et al. [27]Foggy: a platform for workload orchestration in a fog computing environmentFoggy, an architectural framework and software platform based on open source technologiesSupports IoT operations for multitier distributed, heterogeneous, and decentralized cloud computing systems

8Prabadevi et al. [29]Toward blockchain for edge-of-things: a new paradigm, opportunities, and future directionsBlockchain-enabled EoT (BEoT)Enables future low-latency and high-security services and applications

9Feng et al. [30]Attribute-based encryption with parallel outsourced decryption for edge intelligent IoVAttribute-based encryption model with parallel outsourced decryption (ABEM-POD)Improves the speed of outsourced decryption in edge intelligent IoV

10Nguyen et al. [31]Integration of blockchain and cloud of things: architecture, applications and challengesBlockchain and cloud of things integration, called BCoTBCoT increases the efficiency of blockchain technologies