scholarly journals Homomorphic Evaluation of the Integer Arithmetic Operations for Mobile Edge Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Changqing Gong ◽  
Mengfei Li ◽  
Liang Zhao ◽  
Zhenzhou Guo ◽  
Guangjie Han
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Rapid Development ◽  
Heterogeneous Data ◽  
Edge Computing ◽  
Security And Privacy ◽  
Mobile Edge Computing ◽  
Operation Rules ◽  
Original Scheme ◽  
Time Overhead

With the rapid development of the 5G network and Internet of Things (IoT), lots of mobile and IoT devices generate massive amounts of multisource heterogeneous data. Effective processing of such data becomes an urgent problem. However, traditional centralised models of cloud computing are challenging to process multisource heterogeneous data effectively. Mobile edge computing (MEC) emerges as a new technology to optimise applications or cloud computing systems. However, the features of MEC such as content perception, real-time computing, and parallel processing make the data security and privacy issues that exist in the cloud computing environment more prominent. Protecting sensitive data through traditional encryption is a very secure method, but this will make it impossible for the MEC to calculate the encrypted data. The fully homomorphic encryption (FHE) overcomes this limitation. FHE can be used to compute ciphertext directly. Therefore, we propose a ciphertext arithmetic operation that implements data with integer homomorphic encryption to ensure data privacy and computability. Our scheme refers to the integer operation rules of complement, addition, subtraction, multiplication, and division. First, we use Boolean polynomials (BP) of containing logical AND, XOR operations to represent the rulers. Second, we convert the BP into homomorphic polynomials (HP) to perform ciphertext operations. Then, we optimise our scheme. We divide the ciphertext vector of integer encryption into subvectors of length 2 and increase the length of private key of FHE to support the 3-multiplication level additional. We test our optimised scheme in DGHV and CMNT. In the number of ciphertext refreshes, the optimised scheme is reduced by 2/3 compared to the original scheme, and the time overhead of our scheme is reduced by 1/3. We also examine our scheme in CNT of without bootstrapping. The time overhead of optimised scheme over DGHV and CMNT is close to the original scheme over CNT.

scholarly journals When Sensor-Cloud Meets Mobile Edge Computing

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5324 ◽  
Author(s):  
Tian Wang ◽  
Yucheng Lu ◽  
Zhihan Cao ◽  
Lei Shu ◽  
Xi Zheng ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Edge Computing ◽  
Security And Privacy ◽  
Future Research ◽  
Mobile Edge Computing ◽  
Control Center ◽  
Computing Center ◽  
Sensor Cloud ◽  
Evaluation Mechanism ◽  
And Control

Sensor-clouds are a combination of wireless sensor networks (WSNs) and cloud computing. The emergence of sensor-clouds has greatly enhanced the computing power and storage capacity of traditional WSNs via exploiting the advantages of cloud computing in resource utilization. However, there are still many problems to be solved in sensor-clouds, such as the limitations of WSNs in terms of communication and energy, the high latency, and the security and privacy issues due to applying a cloud platform as the data processing and control center. In recent years, mobile edge computing has received increasing attention from industry and academia. The core of mobile edge computing is to migrate some or all of the computing tasks of the original cloud computing center to the vicinity of the data source, which gives mobile edge computing great potential in solving the shortcomings of sensor-clouds. In this paper, the latest research status of sensor-clouds is briefly analyzed and the characteristics of the existing sensor-clouds are summarized. After that we discuss the issues of sensor-clouds and propose some applications, especially a trust evaluation mechanism and trustworthy data collection which use mobile edge computing to solve the problems in sensor-clouds. Finally, we discuss research challenges and future research directions in leveraging mobile edge computing for sensor-clouds.

scholarly journals Efficient of Floading Approach for Resource Allocation and Optimization in Mobile Edge Computing Environment

2021 ◽  
Vol 12 (6) ◽  
pp. 2581-2593
Author(s):  
C. Anuradha, M. Ponnavaikko
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Smart Cities ◽  
Edge Computing ◽  
Cloud Services ◽  
Security And Privacy ◽  
The Internet ◽  
Mobile Edge Computing ◽  
Major Barrier

Cloud computing provides a platform for services and resources over the internet for users. The large pool of data resources and services has enabled the emergence of several novel applications such as smart grids, smart environments, and virtual reality. However, the state-of-the-art of cloud computing faces a delay constraint, which becomes a major barrier for reliable cloud services. This constraint is mostly highlighted in the case of smart cities (SC) and the Internet of Things (IoT). Therefore, the recent cloud computing paradigm has poor performance and cannot meet the low delay, navigation, and mobility support requirements.Machine-to-machine (M2M) connectivity has drawn considerable interest from both academia and industry with a growing number of machine-type communication devices (MTCDs). The data links with M2M communications are usually small but high bandwidth, unlike conventional networking networks, demanding performance management of both energy consumption and computing. The main challenges faced in mobile edge computing are task offloading, congestion control, Resource allocation, security and privacy issue, mobility and standardization .Our work mainly focus on offloading based resource allocation and security issues by analyzing the network parameters like reduction of latency and improvisation of bandwidth involved in cloud environment. The cloudsim simulation tool has been utilized to implement the offload balancing mechanism to decrease the energy consumption and optimize the computing resource allocation as well as improve computing capability.

scholarly journals A Blockchain-Based Trusted Edge Platform in Edge Computing Environment

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2126
Author(s):  
Jinnan Zhang ◽  
Changqi Lu ◽  
Gang Cheng ◽  
Teng Guo ◽  
Jian Kang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Privacy ◽  
Heterogeneous Data ◽  
Edge Computing ◽  
Security And Privacy ◽  
Computing Environment ◽  
Security Technology ◽  
Communication Time ◽  
Computing Platforms ◽  
Multiple Network

Edge computing is a product of the evolution of IoT and the development of cloud computing technology, providing computing, storage, network, and other infrastructure close to users. Compared with the centralized deployment model of traditional cloud computing, edge computing solves the problems of extended communication time and high convergence traffic, providing better support for low latency and high bandwidth services. With the increasing amount of data generated by users and devices in IoT, security and privacy issues in the edge computing environment have become concerns. Blockchain, a security technology developed rapidly in recent years, has been adopted by many industries, such as finance and insurance. With the edge computing capability, deploying blockchain platforms/applications on edge computing platforms can provide security services for network edge environments. Although there are already solutions for integrating edge computing with blockchain in many IoT application scenarios, they slightly lack scalability, portability, and heterogeneous data processing. In this paper, we propose a trusted edge platform to integrate the edge computing framework and blockchain network for building an edge security environment. The proposed platform aims to preserve the data privacy of the edge computing client. The design based on the microservice architecture makes the platform lighter. To improve the portability of the platform, we introduce the Edgex Foundry framework and design an edge application module on the platform to improve the business capability of Edgex. Simultaneously, we designed a series of well-defined security authentication microservices. These microservices use the Hyperledger Fabric blockchain network to build a reliable security mechanism in the edge environment. Finally, we build an edge computing network using different hardware devices and deploy the trusted edge platform on multiple network nodes. The usability of the proposed platform is demonstrated by testing the round-trip time (RTT) of several important workflows. The experimental results demonstrate that the platform can meet the availability requirements in real-world usage scenarios.

scholarly journals A Survey on Mobile Edge Computing: Focusing on Service Adoption and Provision

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Kai Peng ◽  
Victor C. M. Leung ◽  
Xiaolong Xu ◽  
Lixin Zheng ◽  
Jiabin Wang ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Mobile Networks ◽  
Edge Computing ◽  
Computation Offloading ◽  
Battery Life ◽  
Mobile Edge Computing ◽  
Service Adoption ◽  
Comprehensive Survey ◽  
And Storage ◽  
Execution Delay

Mobile cloud computing (MCC) integrates cloud computing (CC) into mobile networks, prolonging the battery life of the mobile users (MUs). However, this mode may cause significant execution delay. To address the delay issue, a new mode known as mobile edge computing (MEC) has been proposed. MEC provides computing and storage service for the edge of network, which enables MUs to execute applications efficiently and meet the delay requirements. In this paper, we present a comprehensive survey of the MEC research from the perspective of service adoption and provision. We first describe the overview of MEC, including the definition, architecture, and service of MEC. After that we review the existing MUs-oriented service adoption of MEC, i.e., offloading. More specifically, the study on offloading is divided into two key taxonomies: computation offloading and data offloading. In addition, each of them is further divided into single MU offloading scheme and multi-MU offloading scheme. Then we survey edge server- (ES-) oriented service provision, including technical indicators, ES placement, and resource allocation. In addition, other issues like applications on MEC and open issues are investigated. Finally, we conclude the paper.

scholarly journals Risk Control Management of New Rural Cooperative Financial Organizations Based on Mobile Edge Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Fanrong Kong ◽  
Hongxia Lu
Keyword(s):  
Cloud Computing ◽  
Mutual Fund ◽  
Network Architecture ◽  
Financial Institution ◽  
Risk Control ◽  
Edge Computing ◽  
Experimental Simulation ◽  
Mobile Edge Computing ◽  
Financial Organization ◽  
Rural Enterprises

Rural cooperative financial organization is a new type of cooperative financial organization in recent years. It is a community financial institution created by farmers and small rural enterprises to voluntarily invest in shares in order to meet the growing demand for rural financing. However, this financial organization has many flaws in the design of the system; it has not promoted the better development of rural mutual fund assistance. In addition, mobile edge computing (MEC) can be used as an effective supplement to mobile cloud computing and has been proposed. However, most of the current literature studies on cloud computing provide computing offload just to propose a network architecture, without modeling and solving to achieve. In this context, this paper focuses on the practical application of MEC in the risk control of new rural cooperative financial organizations. This paper proposes a collaborative LECC mechanism based on machine learning under the MEC architecture. The experimental simulation shows that the HR under the LECC mechanism is about 17%–23%, 46%–69%, and 93%–177% higher than that of LENC, LRU, and RR, respectively. It is unrealistic to want to rely on meager loan interest for long-term development. The most practical way is to increase the income level of the organization itself.

scholarly journals Mobile edge computing for internet of things (IoT): security and privacy issues

2020 ◽  
Vol 18 (3) ◽  
pp. 1486
Author(s):  
Atiqur Rahman ◽  
Guangfu Wu ◽  
Ali Md Liton
Keyword(s):  
Internet Of Things ◽  
Edge Computing ◽  
Security And Privacy ◽  
Mobile Edge Computing ◽  
Security Threat ◽  
Protection Mechanism ◽  
Challenges And Opportunities ◽  
Privacy Issues ◽  
Computing Structure

Nowadays, the masonry for environment-friendly and protected network structure designs, for example, the Internet of Things and gigantic data analytics are increasing at a faster pace compared to an earlier state. Mobile edge computing for an Internet of Things widget is information processing that is achieved at or close to the collectors of information in an Internet of Things system. Herein, we are proposing to temporarily evaluation the concepts, features, protection, and privacy applications of Internet of Things authorized mobile edge computing with its data protection view in our data-driven globe. We focus on illuminating one of kind components that need to be taken into consideration whilst creating a scalable, consistent, impenetrable and disseminated mobile edge computing structure. We also sum up the fundamental ideas regarding security threat alleviation strategies. After that, we walk around the existing challenges and opportunities in the area of mobile edge computing. In conclusion, we analyze a case study, in which a security protection mechanism can be hardened to lift out everyday jobs.

scholarly journals Container-Based Fast Service Migration Method for Mobile Edge Computing

2021 ◽  
Author(s):  
Xianyu Meng ◽  
Wei Lu
Keyword(s):  
Dynamic Loading ◽  
File System ◽  
High Reliability ◽  
Rapid Development ◽  
Edge Computing ◽  
Migration Time ◽  
Mobile Edge Computing ◽  
Computing Center ◽  
Service Migration ◽  
Iot Devices

Mobile edge computing (MEC) provides users with low-latency, high-bandwidth, and high-reliability services by migrating the computing power of the cloud computing center to the edge of the network. It is thus being considered an effective solution for the contradiction between the limited computing capabilities of Internet of Things (IoT) devices and the rapid development of delay-sensitive real-time applications. In this study, we propose and design a container union file system based on the differencing hard disk and dynamic loading strategy to address the excessively long migration time caused by the bundling transmission of the file system and container images during container-based service migration. The proposed method involves designing a mechanism based on a remote dynamic loading strategy to avoid the downloading of all container images, thereby reducing the long preparation time before which stateless migration can begin. Furthermore, in view of the excessive latency of the edge service during the stateful migration process, a strategy for avoiding the transmission of the underlying file system and container images is designed to optimize the service interruption time and service quality degradation time. Experiments show that the proposed method and strategy can effectively reduce the migration time of container-based services.

scholarly journals Enhancing cloud computing security by paillier homomorphic encryption

2021 ◽  
Vol 11 (2) ◽  
pp. 1771
Author(s):  
Muna Mohammed Saeed Altaee ◽  
Mafaz Alanezi
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Security And Privacy ◽  
Proxy Server ◽  
Process Data ◽  
Encrypted Data ◽  
Rsa Algorithm ◽  
Encryption Algorithms ◽  
Will Force ◽  
Mathematical Operations

In recent years, the trend has increased for the use of cloud computing, which provides broad capabilities with the sharing of resources, and thus it is possible to store and process data in the cloud remotely, but this (cloud) is untrusted because some parties can connect to the network such as the internet and read or change data because it is not protected, therefore, protecting data security and privacy is one of the challenges that must be addressed when using cloud computing. Encryption is interested in the field of security, confidentiality and integrity of information that sent by a secure connection between individuals or institutions regardless of the method used to prepare this connection. But using the traditional encryption methods to encrypt the data before sending it will force the data provider to send his private key to the server to decrypt the data to perform computations on it. In this paper we present a proposal to secure banking data transmission through the cloud by using partially homomorphic encryption algorithms such as (paillier, RSA algorithm) that allow performing mathematical operations on encrypted data without needing to decryption. A proxy server will also use for performing re-encryption process to enhance security.

scholarly journals Selective Offloading by Exploiting ARIMA-BP for Energy Optimization in Mobile Edge Computing Networks

Algorithms ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 48 ◽  
Author(s):  
Ming Zhao ◽  
Ke Zhou
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Mobile Devices ◽  
Energy Optimization ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Innovative Technique ◽  
Simulation Results ◽  
Bp Model

Mobile Edge Computing (MEC) is an innovative technique, which can provide cloud-computing near mobile devices on the edge of networks. Based on the MEC architecture, this paper proposes an ARIMA-BP-based Selective Offloading (ABSO) strategy, which minimizes the energy consumption of mobile devices while meeting the delay requirements. In ABSO, we exploit an ARIMA-BP model for estimating computation capacity of the edge cloud, and then design a Selective Offloading Algorithm for obtaining offloading strategy. Simulation results reveal that the ABSO can apparently decrease the energy consumption of mobile devices in comparison with other offloading methods.

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