scholarly journals Security-Aware computation offloading for Mobile edge computing-Enabled smart city

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Kai Peng ◽  
Peichen Liu ◽  
Peng Tao ◽  
Qingjia Huang
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Living Standards ◽  
Computation Offloading ◽  
Smart Devices ◽  
Time Consumption ◽  
Delay Sensitive ◽  
Consumption Energy ◽  
Overall Performance

AbstractSmart city has obtained increasing attention from both academic and industry which has the potential to improve human living standards. A smart city consists of a great number of smart devices which are generating large amounts of data and emerging applications all the time. However, the computing capacity of smart devices are limited. Fortunately, the emergence of MEC can solve the above problem. However, the resources of edge servers in MEC are limited and the capabilities of edge servers are heterogeneous. It is important to improve the average resource utilization of all edge servers and keep load balancing of edge server cluster simultaneously. On the other hand, quite a few numbers of applications are delay-sensitive, it is necessary to ensure the security of these applications. In this paper, we consider joint optimization of mobile device and edge server in MEC-enabled smart city, improving the overall performance of the system. Technically, a new multi-objective computation offloading method is implemented to reduce time consumption, energy consumption, and keep load balancing of edge servers, as well as increase average resource utilization of edge servers while meeting the deadline constraint of delay-sensitive applications. Sufficient experiments have been conducted to prove the effectiveness and superiority of our proposed method in different scenarios.

M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities

2021 ◽  
pp. 1-15
Author(s):  
Subhranshu Sekhar Tripathy ◽  
Diptendu Sinha Roy ◽  
Rabindra K. Barik
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Smart City ◽  
Load Transfer ◽  
Smart Cities ◽  
Fog Computing ◽  
Round Robin ◽  
Healthcare Management ◽  
Optimization Strategy ◽  
Allocation Method

Nowadays, cities are intended to change to a smart city. According to recent studies, the use of data from contributors and physical objects in many cities play a key element in the transformation towards a smart city. The ‘smart city’ standard is characterized by omnipresent computing resources for the observing and critical control of such city’s framework, healthcare management, environment, transportation, and utilities. Mist computing is considered a computing prototype that performs IoT applications at the edge of the network. To maintain the Quality of Service (QoS), it is impressive to employ context-aware computing as well as fog computing simultaneously. In this article, the author implements an optimization strategy applying a dynamic resource allocation method based upon genetic algorithm and reinforcement learning in combination with a load balancing procedure. The proposed model comprises four layers i.e. IoT layer, Mist layer, Fog layer, and Cloud layer. Authors have proposed a load balancing technique called M2F balancer which regulates the traffic in the network incessantly, accumulates the information about each server load, transfer the incoming query, and disseminate them among accessible servers equally using dynamic resources allocation method. To validate the efficacy of the proposed algorithm makespan, resource utilization, and the degree of imbalance (DOI) are considered as the scheduling parameter. The proposed method is being compared with the Least count, Round Robin, and Weighted Round Robin. In the end, the results demonstrate that the solutions enhance QoS in the mist assisted cloud environment concerning maximization resource utilization and minimizing the makespan. Therefore, M2FBalancer is an effective method to utilize the resources efficiently by ensuring uninterrupted service. Consequently, it improves performance even at peak times.

Resource Management Techniques to Manage the Load Balancing in Cloud Computing

2019 ◽  
pp. 170-195
Author(s):  
Pradeep Kumar Tiwari ◽  
Sandeep Joshi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Distributed System ◽  
User Satisfaction ◽  
Single Node ◽  
Load Imbalance ◽  
Management Techniques ◽  
Overall Performance ◽  
Utilization Ratio

Load balancing is one of the vital issues in cloud computing that needs to be achieved using proper techniques as it is directly related to higher resource utilization ratio and user satisfaction. By evenly distributing the dynamic local workload across all the nodes in the whole cloud, load balancing makes sure that no single node is overwhelmed, and some other nodes are kept idle. Hence, the technique helps to improve the overall performance resource utility of the system which will lead to high user satisfaction and resource utilization ratio. It also ensures the fair and effective distribution of each and every computing resource in the distributed system. Furthermore, the various load balancing techniques prevent the possible bottlenecks of the system created by the load imbalance. Maximization of the throughput, minimization of the response time, and avoidance of the overload are the other major advantages of the load balancing. Above all, by keeping resource consumption at the minimum, the load balancing techniques help to reduce costs.

scholarly journals The network architecture optimization based on the server load balancing technology

2021 ◽  
Vol 336 ◽  
pp. 08001
Author(s):  
Ruicai Huo ◽  
Songqiu Liu ◽  
Shiwei He
Keyword(s):  
Load Balancing ◽  
Resource Utilization ◽  
Network Architecture ◽  
Integration Method ◽  
Single Point ◽  
Gateway System ◽  
Architecture Optimization ◽  
Cluster Design

The paper takes the authentication gateway system for internal office network as the research object, for the performance bottleneck and single point of failure problem of the single authentication gateway deployed in the existing primary and standby modes, chooses an authentication gateway integration method based on CA certificate. The practical results show that: through implementing the authentication gateway cluster design and introducing load balancing mechanism, this method solves the performance, stability and single point of failure of the authentication gateway, and improves the resource utilization of the authentication gateway device. This method introduced in this paper can be used for reference for the network architecture optimization based on the server load balancing technology.

Smart cities: existing security problems and their solutions

2020 ◽  
Vol 60 (11) ◽  
pp. 16-20
Author(s):  
Vugar Hajimahmud Abdullayev ◽  
◽  
Vusala Alyag Abuzarova ◽  
Keyword(s):  
Internet Of Things ◽  
Cyber Security ◽  
Smart City ◽  
Information Technologies ◽  
New Technologies ◽  
Smart Cities ◽  
Smart Devices ◽  
The Internet ◽  
It Industry ◽  
Internet Of Things Technology

The article is devoted to the study of cyber security problems in the Smart Cities system. The development of the IT industry has led to the introduction of new technologies into our lives. One of these technologies is the Internet of Things technology. The application of IoT technology has increased in recent years. One of the most important areas in which Internet of Things technology is applied is the Smart Cities system. The main difference between smart cities and other cities is that their components are connected to each other via the Internet. All these smart devices create a smart city system in general. One of the biggest and most important problems in many areas where the Internet is used is security. The article looks at possible security problems in the system of smart cities and solutions to ensure cyber security. Key words: Smart city; Internet of Things; Information technologies; Security; Cyber security

Two-tier end-edge collaborative computation offloading for edge computing

2021 ◽  
pp. 1-12
Author(s):  
Yong Xiao ◽  
Ling Wei ◽  
Junhao Feng ◽  
Wang En
Keyword(s):  
Computing System ◽  
End Users ◽  
Edge Computing ◽  
Computation Offloading ◽  
Iot Applications ◽  
Delay Sensitive ◽  
Task Processing ◽  
Queue Lengths ◽  
The Stability ◽  
The Cost

Edge computing has emerged for meeting the ever-increasing computation demands from delay-sensitive Internet of Things (IoT) applications. However, the computing capability of an edge device, including a computing-enabled end user and an edge server, is insufficient to support massive amounts of tasks generated from IoT applications. In this paper, we aim to propose a two-tier end-edge collaborative computation offloading policy to support as much as possible computation-intensive tasks while making the edge computing system strongly stable. We formulate the two-tier end-edge collaborative offloading problem with the objective of minimizing the task processing and offloading cost constrained to the stability of queue lengths of end users and edge servers. We perform analysis of the Lyapunov drift-plus-penalty properties of the problem. Then, a cost-aware computation offloading (CACO) algorithm is proposed to find out optimal two-tier offloading decisions so as to minimize the cost while making the edge computing system stable. Our simulation results show that the proposed CACO outperforms the benchmarked algorithms, especially under various number of end users and edge servers.

Hierarchical Load Balancing Model by Optimal Resource Utilization

2021 ◽  
pp. 150-164
Author(s):  
Jagdish Chandra Patni
Keyword(s):  
Load Balancing ◽  
Grid Computing ◽  
Resource Utilization ◽  
Resource Availability ◽  
High Performance ◽  
Low Cost ◽  
Original Form ◽  
Computing Paradigm ◽  
Optimal Resource ◽  
Performance Computing

Powerful computational capabilities and resource availability at a low cost is the utmost demand for high performance computing. The resources for computing can viewed as the edges of an interconnected grid. It can attain the capabilities of grid computing by balancing the load at various levels. Since the nature of resources are heterogeneous and distributed geographically, the grid computing paradigm in its original form cannot be used to meet the requirements, so it can use the capabilities of the cloud and other technologies to achieve the goal. Resource heterogeneity makes grid computing more dynamic and challenging. Therefore, in this article the problem of scalability, heterogeneity and adaptability of grid computing is discussed with a perspective of providing high computing, load balancing and availability of resources.

scholarly journals A Resource Oriented Route Selection Framework Using Contextual Information Based on Fuzzy Logic

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1023 ◽  
Author(s):  
Khadak Singh Bhandari ◽  
Gi Hwan Cho
Keyword(s):  
Fuzzy Logic ◽  
Objective Function ◽  
Smart City ◽  
Contextual Information ◽  
Network Dynamics ◽  
Residual Energy ◽  
Smart Devices ◽  
Route Selection ◽  
Network Simulator ◽  
Lossy Networks

Internet of Things (IoT) is expected to have a significant impact on city’s service provisioning and make a smart city more accessible and pragmatic since the deployment of heterogeneous smart devices in each infrastructure of cities is increasing. So far, the IPv6 routing protocol for low power and lossy networks (RPL) is considered to fit on IoT infrastructure for achieving the expected network requirements. While RPL meets the IoT network requirements quite well, there are some issues that need to be addressed, such as adaptability to network dynamics. This issue significantly limits the use of RPL in many smart city application scenarios, such as emergency alerts with high traffic flows. As part of a smart city vision, IoT applications are becoming more diverse, which requires context-awareness in routing protocols to support the behavior of the network. To address this issue, we design an objective function that performs the route selection based on fuzzy logic techniques while using contextual information from the application. For this, we present a new context-oriented objective function (COOF) that comprises both nodes as well as link metrics. Further, we suggest two new routing metrics, known as queue fluctuation index (QFI) and residual energy index (REI), which consider the status of queue utilization and remaining energy, respectively. The metrics used are designed to respond to the dynamic needs of the network. The proposed approach has been examined and evaluated in different scenarios when compared to other similar approach and default RPL objective functions. Simulation experiments are conducted in Cooja network simulator for Contiki OS. The evaluation results show that COOF can cope with network dynamics and IoT-based smart city application requirements.

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