An Efficient Secure Message Transmission in Mobile Ad Hoc Networks using Enhanced Homomorphic Encryption Scheme

In MANETs the nodes are capable of roaming independently. The node with inadequate physical protection can be easily captured, compromised and hijacked. Due to this huge dependency's on the nodes, there are more security problems. Therefore the nodes in the network must be prepared to work in a mode that trusts no peer. In this paper we look at the current scheme to transmit the data in MANETs. We then propose a new scheme for secure transmission of message in MANETs as Alternative scheme for DF2019;s new Ph and DF2019;s additive and multiplicative PH. Here we also provide the computational cost of the homomorphic encryption schemes. We also provide the implementation issues of our new scheme in MANETs. For the entire message to be recoverd by the attacker, the attacker needs to compromise atleast g nodes, one node from each group g and know the encryption keys to decrypt the message. The success rate of our proposed new scheme is 100% if there are more number of active paths in each group of the network

SenMinCom: Pervasive Distributed Dynamic Sensor Data Mining for Effective Commerce

In last few years, the use of wireless sensor networks and cell phones has become ubiquitous; fusing these technologies in the field of business will open up new possibilities. To fill this lacuna, I propose a novel idea where the combination of these will facilitate companies to receive feedback on their products and services. System\u27s unobtrusive sensors will not only collect shopping, mobile usage data from consumers but will also make effective use of this information to increase revenue, cut costs, etc.; the use of mobile agent based data mining allows analyzing the data from different dimensions, categorizing it on factors such as product positioning, promotion of goods, etc. as in the case of a shopping store. Additionally, because of the dynamic mining system the companies get on-the-scene recommendation of products rather than off-the-scene. In this thesis, a novel distributed pervasive mining system is proposed to get dynamic shopping information and mobile device usage of the customers

Design and implementation of a multi-agent opportunistic grid computing platform

Opportunistic Grid Computing involves joining idle computing resources in enterprises into a converged high performance commodity infrastructure. The research described in this dissertation investigates the viability of public resource computing in offering a plethora of possibilities through seamless access to shared compute and storage resources. The research proposes and conceptualizes the Multi-Agent Opportunistic Grid (MAOG) solution in an Information and Communication Technologies for Development (ICT4D) initiative to address some limitations prevalent in traditional distributed system implementations. Proof-of-concept software components based on JADE (Java Agent Development Framework) validated Multi-Agent Systems (MAS) as an important tool for provisioning of Opportunistic Grid Computing platforms. Exploration of agent technologies within the research context identified two key components which improve access to extended computer capabilities. The first component is a Mobile Agent (MA) compute component in which a group of agents interact to pool shared processor cycles. The compute component integrates dynamic resource identification and allocation strategies by incorporating the Contract Net Protocol (CNP) and rule based reasoning concepts. The second service is a MAS based storage component realized through disk mirroring and Google file-system’s chunking with atomic append storage techniques. This research provides a candidate Opportunistic Grid Computing platform design and implementation through the use of MAS. Experiments conducted validated the design and implementation of the compute and storage services. From results, support for processing user applications; resource identification and allocation; and rule based reasoning validated the MA compute component. A MAS based file-system that implements chunking optimizations was considered to be optimum based on evaluations. The findings from the undertaken experiments also validated the functional adequacy of the implementation, and show the suitability of MAS for provisioning of robust, autonomous, and intelligent platforms. The context of this research, ICT4D, provides a solution to optimizing and increasing the utilization of computing resources that are usually idle in these contexts

Q-learning Based System for Path Planning with UAV Swarms in Obstacle Environments

Path Planning methods for autonomous control of Unmanned Aerial Vehicle (UAV) swarms are on the rise because of all the advantages they bring. There are more and more scenarios where autonomous control of multiple UAVs is required. Most of these scenarios present a large number of obstacles, such as power lines or trees. If all UAVs can be operated autonomously, personnel expenses can be decreased. In addition, if their flight paths are optimal, energy consumption is reduced. This ensures that more battery time is left for other operations. In this paper, a Reinforcement Learning based system is proposed for solving this problem in environments with obstacles by making use of Q-Learning. This method allows a model, in this particular case an Artificial Neural Network, to self-adjust by learning from its mistakes and achievements. Regardless of the size of the map or the number of UAVs in the swarm, the goal of these paths is to ensure complete coverage of an area with fixed obstacles for tasks, like field prospecting. Setting goals or having any prior information aside from the provided map is not required. For experimentation, five maps of different sizes with different obstacles were used. The experiments were performed with different number of UAVs. For the calculation of the results, the number of actions taken by all UAVs to complete the task in each experiment is taken into account. The lower the number of actions, the shorter the path and the lower the energy consumption. The results are satisfactory, showing that the system obtains solutions in fewer movements the more UAVs there are. For a better presentation, these results have been compared to another state-of-the-art approach

Eco Models in Heteregeneous Peer-topeer (P2P) Systems

研究成果の概要 (和文) : 情報システムは、コンピュータ、センサ等の種々の情報機器を含んだ異種なものとなってきている。こうしたシステムでは、これまでの応答時間、スループット等の性能目標に加えて、新たにシステム全体の消費電力の低減が重要となってきている。本研究では、自律的な対等なプロセスから構成される完全分散型の大規模P2Pシステムを考える。ピア間の自律的な協調動作により、システム全体の消費電力を低減できる分散型システムの新しいモデル、特に消費電力については実際のコンピュータの消費電力の実測に基づいて、消費電力のモデルの構築を行った。このモデルに基づいて、ピア間の分散型の協調動作方式を研究し、評価を行った。研究成果の概要 (英文) : Information systems are composed of nodes like computers and sensors interconnected in networks. Here, we have to reduce the total electric energy consumed by nodes in addition to achieving traditional performance objectives. In this research, we proposed a power consumption model of a node to perform application processes. We first measure the total electric power of types of computers to perform application processes and then abstract essential parameters which dominate the power consumed by nodes. The power consumption model which we proposed is referred to as simple power consumption (SPC) model. Here, a computer consumes maximum poser [W] if at least one process is performed, otherwise consumes minimum power. Based on the SPC model, we proposed the energy-aware server selection (EA) algorithm and evaluated the EA model. In the evaluation, we showed not only the total power consumption of a server cluster but also the average execution time of each process are reduced

サーバクラスタでの低消費電力化のための移行モデルの研究

博士(工学)法政大学 (Hosei University

Adaptive Middleware for Resource-Constrained Mobile Ad Hoc and Wireless Sensor Networks

Mobile ad hoc networks: MANETs) and wireless sensor networks: WSNs) are two recently-developed technologies that uniquely function without fixed infrastructure support, and sense at scales, resolutions, and durations previously not possible. While both offer great potential in many applications, developing software for these types of networks is extremely difficult, preventing their wide-spread use. Three primary challenges are: 1) the high level of dynamics within the network in terms of changing wireless links and node hardware configurations,: 2) the wide variety of hardware present in these networks, and: 3) the extremely limited computational and energy resources available. Until now, the burden of handling these issues was put on the software application developer. This dissertation presents three novel programming models and middleware systems that address these challenges: Limone, Agilla, and Servilla. Limone reliably handles high levels of dynamics within MANETs. It does this through lightweight coordination primitives that make minimal assumptions about network connectivity. Agilla enables self-adaptive WSN applications via the integration of mobile agent and tuple space programming models, which is critical given the continuously changing network. It is the first system to successfully demonstrate the feasibility of using mobile agents and tuple spaces within WSNs. Servilla addresses the challenges that arise from WSN hardware heterogeneity using principles of Service-Oriented Computing: SOC). It is the first system to successfully implement the entire SOC model within WSNs and uniquely tailors it to the WSN domain by making it energy-aware and adaptive. The efficacies of the above three systems are demonstrated through implementation, micro-benchmarks, and the evaluation of several real-world applications including Universal Remote, Fire Detection and Tracking, Structural Health Monitoring, and Medical Patient Monitoring