A GRASP Algorithm Based on New Randomized Heuristic for Vehicle Routing Problem

This paper presents a novel GRASP algorithm based on a new randomized heuristic for solving the capacitated vehicle routing problem, which characterized by using a fleet of homogenous vehicle capacity that will start from one depot, to serve a number of customers with demands that are less than the vehicle capacity. The proposed method is based on a new constructive heuristic and a simulated annealing procedure as an improvement phase. The new constructive heuristic uses four steps to generate feasible initial solutions, and the simulated annealing enhances these solutions found to reach the optimal one. We tested our algorithm on two sets of benchmark instances and the obtained results are very encouraging

A generalized island model based on parallel and cooperating metaheuristics for effective large capacitated vehicle routing problem solving

Capacitated Vehicle Routing Problem (CVRP) is among transportation problems that are of the foremost concerns in logistics. Ensuring an effective product distribution over a large distribution network while reducing the required costs represents the scope of the present work. A synergic and interactive environment of parallel meta-heuristics is developed using a generalized island model to deal with large instances of CVRP. In the proposed model, cooperative meta-heuristics, namely genetic algorithms (GA) and ant colony optimization algorithms (ACO), are organized into archipelagoes. They communicate synchronously, globally and locally by exchanging solutions. In order to handle properly the migration of solutions, either between archipelagoes or between islands within the same archipelago, appropriate selection and replacement policies are adopted. Furthermore, the proposed approach uses other new features including a new binary solution representation and different optimization process (i.e GA, ACO) on each island. To prove the efficiency of the present work, tests over the well-known set of benchmarks, comparative studies and experimental analysis have been conducted.230

Customized blockchain-based architecture for secure smart home for lightweight IoT

Safeguarding security and privacy remains a major challenge with regards to the Internet of Things (IoT) primarily due to the large scale and distribution of IoT networks. The information systems in Smart Homes are mainly based on sharing information through smart devices (IoT) and embedded sensors. Each sensor generates data to be processed or assembled by a central system. This data, while being transmitted over the internet to other users or servers, can be compromised for its privacy, user confidentiality and/or service availability. This paper proposes a novel Blockchain-based solution for secure smart home systems, using a combined hyperledger fabric and hyperledger composer. This solution is designed to overcome reported security limitations in commonly used permissioned blockchains approaches. The proposed architecture contains four layers: Cloud storage, Hyperledger fabric, Hyperledger composer, and a smart home layer. Another important aspect of the proposed solution is the mapping of the attributes of a smart home to those from the hyperledger composer. This mapping allows for a customized, designed-for-purpose solution which can meet the security requirements for IoT based smart homes. The proposed architecture was implemented and tested to improve the integrity, confidentiality, availability, authorization and privacy of smart homes as well as some inherited features, including transparency and interoperability

Blockchain for Modern Applications: A Survey

Blockchain is a modern technology that has revolutionized the way society interacts and trades. It could be defined as a chain of blocks that stores information with digital signatures in a distributed and decentralized network. This technique was first adopted for the creation of digital cryptocurrencies, such as Bitcoin and Ethereum. However, research and industrial studies have recently focused on the opportunities that blockchain provides in various other application domains to take advantage of the main features of this technology, such as: decentralization, persistency, anonymity, and auditability. This paper reviews the use of blockchain in several interesting fields, namely: finance, healthcare, information systems, wireless networks, Internet of Things, smart grids, governmental services, and military/defense. In addition, our paper identifies the challenges to overcome, to guarantee better use of this technology

Leveraging a cloud-native architecture to enable semantic interconnectedness of data for cyber threat intelligence

Cloud technologies have several merits including the elimination of cost incurred when traditional technologies are adopted. Despite the benefits, the cloud is still facing security challenges thereby calling for cyber threat intelligence capable of identifying threats and providing possible solutions. However, dependence on traditional security mechanisms and approaches for security solutions within cloud environments presents challenges. This calls for cloud-native solutions which leverages cloud features for design and development of solutions for data and applications hosted and running within the cloud. Past studies have suggested the adoption of semantic technologies for cloud-based security mechanisms. However, the semantic processing of data faces challenges of data interconnectedness due to aggregation of data from diverse heterogenous sources. Hence, this study proposes a cloud-native architecture capable of connecting security-related data from different sources in the cloud to enhance cyber threat intelligence. It presents a proof-of-concept implementation of the proposed solution on Amazon AWS cloud, within an auto-scaling group for scalability and across multiple availability zones for high availability

Multilevel Central Trust Management Approach for Task Scheduling on IoT-Based Mobile Cloud Computing

With the increasing number of mobile devices and IoT devices across a wide range of real-life applications, our mobile cloud computing devices will not cope with this growing number of audiences soon, which implies and demands the need to shift to fog computing. Task scheduling is one of the most demanding scopes after the trust computation inside the trustable nodes. The mobile devices and IoT devices transfer the resource-intensive tasks towards mobile cloud computing. Some tasks are resource-intensive and not trustable to allocate to the mobile cloud computing resources. This consequently gives rise to trust evaluation and data sync-up of devices joining and leaving the network. The resources are more intensive for cloud computing and mobile cloud computing. Time, energy, and resources are wasted due to the nontrustable nodes. This research article proposes a multilevel trust enhancement approach for efficient task scheduling in mobile cloud environments. We first calculate the trustable tasks needed to offload towards the mobile cloud computing. Then, an efficient and dynamic scheduler is added to enhance the task scheduling after trust computation using social and environmental trust computation techniques. To improve the time and energy efficiency of IoT and mobile devices using the proposed technique, the energy computation and time request computation are compared with the existing methods from literature, which identified improvements in the results. Our proposed approach is centralized to tackle constant SyncUPs of incoming devices’ trust values with mobile cloud computing. With the benefits of mobile cloud computing, the centralized data distribution method is a positive approach