Touraj Khodadadi

Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization

A wireless sensor network (WSN) is a collection of sensor nodes that dynamically self-organize themselves into a wireless network without the utilization of any preexisting infrastructure. One of the major problems in WSNs is the energy consumption, whereby the network lifetime is dependent on this factor. In this paper, we propose an optimal routing protocol for WSN inspired by the foraging behavior of ants. The ants try to find existing paths between the source and base station. Furthermore, we have combined this behavior of ants with fuzzy logic in order for the ants to make the best decision. In other words, the fuzzy logic is applied to make the use of these paths optimal. Our algorithm uses the principles of the fuzzy ant colony optimization routing (FACOR) to develop a suitable problem solution. The performance of our routing algorithm is evaluated by Network Simulator 2 (NS2). The simulation results show that our algorithm optimizes the energy consumption amount, decreases the number of routing request packets, and increases the network lifetime in comparison with the original AODV.

Efficient intelligent energy routing protocol in wireless sensor networks

In wireless sensor networks energy is a very important issue because these networks consist of lowpower sensor nodes. This paper proposes a new protocol to reach energy efficiency. The protocol has a different priority in energy efficiency as reducing energy consumption in nodes, prolonging lifetime of the whole network, increasing system reliability, increasing the load balance of the network, and reducing packet delays in the network. In the new protocol is proposed an intelligent routing protocol algorithm. It is based on reinforcement learning techniques. In the first step of the protocol, a new clustering method is applied to the network and the network is established using a connected graph. Then data is transmitted using the Q-value parameter of reinforcement learning technique. The simulation results show that our protocol has improvement in different parameters such as network lifetime, packet delivery, packet delay, and network balance.

Code analysis of lightweight encryption algorithms using in RFID systems to improve cipher performance

This research has investigated the performance analysis of lightweight encryption algorithms, which are using in RFID applications. In the first part, the codes of the investigated ciphers are analyzed, and then, four encryption algorithms include TEA, HIGHT, KATAN, and KLEIN are implemented on AVR Microcontroller to evaluate the number of CPU clock cycle for each cipher. In the last part, the results of two previous parts are compared.

Cloud computing: Vision, architecture and Characteristics

Cloud computing is an unprecedented paradigm for hosting and delivering resources by providing on-demand services. The rapid growth of using cloud-based services in recent years is an impossible fact to be denied as it has increased the efficiency in accessing to shared pools of configurable computing resources. According to this rapid growth, it is anticipated that cloud computing will be the most important and challenging issue in IT industry. Therefore, the state-of-the-art of cloud computing has been surveyed in this paper that involves definition and essential concepts, architecture, models, deployment types, key technologies and characteristics of cloud computing.

Feasibility of Implementing Multi-factor Authentication Schemes in Mobile Cloud Computing

Mobile cloud computing is a new computing technology, which provides on-demand resources. Nowadays, this computing paradigm is becoming one the most interesting technology for IT enterprises. The idea of computing and offloading data in cloud computing is utilized to overcome the inherent challenges in mobile computing. This is carried out by utilizing other resource providers besides the mobile device to host the delivery of mobile applications. However, this technology introduces some opportunities as new computing concept, several challenges, including security and privacy are raised from the adoption of this IT paradigm. Authentication plays an important role to mitigate security and privacy issue in the mobile cloud computing. Even some authentication algorithms are proposed for mobile cloud computing, but most of these algorithms designed for traditional computing models, and are not using cloud capabilities. In mobile cloud computing, we access to pooled computation resources and applying more complicated authentication schemes is possible. Using different authentication factors, which is called multi-factor authentication algorithms, has been proposed for various areas. In this paper, feasibility of implementation of different kinds of multi-factor authentication protocols are discussed. Furthermore, the security and privacy of these algorithms are analyzed. Finally, some future directions are recommended.

Anomaly detection in Online Social Networks using structure-based technique

Online Social Networks as new phenomenon have affected our life in many positive ways; however it can be considered as way of malicious activities. Identifying anomalous users has become a challenge and many researches are conducted but they are not enough and in this paper we propose a methodology based on graph metrics of online social networks. The experimental results illustrate that majority of friends in online social networks have common friends with their friends while anomalous users may not follow this fact.

A comparative study of time management and energy consumption in mobile cloud computing

The effectiveness and influence rate of cloud computing services in devices with limited power and computation resources (e.g. mobile devices) has been considered by many researchers and has led to many performed researches and IT products for these devices. One of the most challenging issues during migration of applications and processes to clouds is the rate energy consumption and time management in comparison with local applications. In this paper, a comparative experimental study has been presented to compare the rate of energy consumption and total execution time in mobile cloud computing and local devices. Hence, three cloud-based environments and two mobile devices with various computation resources were selected to host a cryptography application. Furthermore, cloud-based servers were selected in several places with different distance from the experiment site to investigate the effect of distance and number of hops in the performance of application. The application was run 25 times with different size of plain text to determine the performance of each environment during various workloads. The results showed that the rate of energy consumption and execution time were reduced significantly in cloud-based environments regarding to limited computation resources of mobile devices. This decrease was more considerable when the number of workloads had been increased.

A dynamic classification index to enhance data protection procedures in cloud-based environments

Security is one of the most challenging issues in cloud-based environments and the most important obstacle for advancement of IT-based on-demand services. Classification of data based on attributes is a challenging issues that can improve the rate of reliability and efficiency in cloud computing environments as an emerging technology. Accordingly, a dynamic index classification model has been presented in this paper to ensure data security in cloud computing environments based on their attributes. Index Classification (IC) value has been defined based on three parameters (i.e. data confidentiality, data integrity, and data availability) and various sub-parameters to classify data into 4 main groups. The evaluation procedure of the suggested model involves two main parameters: functionality, and security. Each parameter was examined by simulation processes to investigate strengths and weaknesses of this model in comparison with current models. In overall, the results show that this model has met defined demands of this research to enhance the reliability and efficiency of data protection in cloud computing environments.

VDCI: Variable data classification index to ensure data protection in cloud computing environments

One of the most considerable concerns in cloud computing environments is ensuring about the security and privacy of stored data in cloud servers. Hence, several data protection tools and techniques have been presented to enhance the reliability in this emerging technology. One of the most challenging issues in this area is classification of stored data to improve the efficiency of data protection procedure and reduce energy consumption by eliminating un-necessary processes. Accordingly, a variable data classification index has been defined and presented in this paper to classify stored data in cloud servers dynamically and increase the efficiency of this process. The suggested index uses three main parameters (Data Confidentiality, Data Integrity, and Data Availability) and several sub-parameters to determine the value of this index dynamically according to the specifications of stored data. The proposed classification index was evaluated by functionality and security parameters. In overall, the results show that the suggested index has considerable benefits in the process of data classification in cloud computing environments.

SUAS: Scalable user authentication scheme for secure accessing to cloud-based environments

Cloud computing is an emerging technology that uses the concepts of virtualization, storage, and sharing to store and share resources between users and enterprises. This newfound technology is still unclear to many security problems and one of the most challenging issues in these environments is the reliability of the user authentication process. Therefore, this paper offers an efficient and scalable user authentication scheme for cloud-based environments. The proposed model uses the concepts of agents, cryptography, and key exchanging to enhance and improve the performance of the user authentication and the rate of scalability in cloud-based environments respectively. For achieving to this purpose, the proposed model has been presented based on three main agents: first user authentication agent, second user authentication agent and key manager agent. These agents have divided the process of user authentication and managing keys into several parts to improve the rate of efficiency in this process. Furthermore, the suggested model tries to resist against possible attacks. SUAS, as the suggested model was introduced and simulated in this paper for evaluating the performance and security of the scheme. In overall, the results show that the proposed model has considerable advantages for using in cloud-based environment to increase the salacity, reliability and efficiency of cloud computing models as an emerging technology.