Communication and networking

"Proxy Mobile IPv6 (PMIPv6) was standardized by the Internet Engineering Task
Force (IETF) NetLMM WG as a Network-based Mobility management protocol.
This protocol allows the Mobile Node (MN) to maintain service connectivity while
moving within the PMIPv6 domain. PMIPv6 mobility management is different from
the Host-based Mobility management protocols; where the mobility signaling
management is controlled by the serving network on behalf of the MN. PMIPv6
introduced new network entities to handle the signaling on behalf of the MN.
However, PMIPv6 protocol can only manage the MN’s reachability within a local
domain (intra-domain). If the MN moves beyond the perimeter of PMIPv6 domain,
the mobility support will be lost. Thus, it is an imperative need to develop PMIPv6
to support interconnecting neighboring domains, which provide MN continuous
support across domains. We propose an inter-domain handover scheme to reduce the
handover latency in vehicular environment. The proposed scheme utilizes the Media
Independent Information Service (MIIS) to help the vehicle store information about
the network that it is attached with. Furthermore, the Local Mobile Anchor (LMA)
will use Fully Qualified Domain Name (FQDN).
Keywords: PMIPv6, MIIS, Mobility Management FQDN, DNS"

IP mobility management protocols (e.g. host based mobility protocols) incur significant handover latency, thus aggravate QoS for end user devices. Proxy Mobile IPv6 (PMIPv6) was proposed by the Internet Engineering Task Force (IETF) as a new network-based mobility protocol to reduce the host based handover latency. However the current PMIPv6 cannot support the vehicles high mobility while the vehicles motion within PMIPv6 domain. In this paper we introduce a novel intra-domain PMIPv6 handover technique based vehicular network using Media Independent Handover (MIH). The novel intra-domain PMIPv6 handover based vehicular network improves the handover performance of PMIPv6 by allowing the new PMIPv6 domain to obtain the MIIS information to estimate whether the handover is necessary or not before the vehicles movement to the second MAG of the new PMIPv6 domain. We evaluate the handover latency and data packet loss of the proposed handover process compared to PMIPv6. The conducted analysis results confirm that the novel handover process yields the reduced handover latency compared to that of PMIPv6 and also prevents data packet loss.

Proxy Mobile IPv6 (PMIPv6) was proposed by the Internet Engineering Task Force (IETF) as a new network-based mobility protocol which does not require the involvement of MN’s in any form of mobility management. MN can handover relatively faster in PMIPv6 than in host-based mobility protocols (e.g. Mobile IPv6 (MIPv6)) because it actively uses link-layer attachment information which reduces the movement detection time, and eliminates duplicate address detection procedures. However, the current PMIPv6 cannot provide continuous mobility support for MN when roaming between different PMIPv6 domains; we introduce a novel inter-domain PMIPv6 scheme to support seamless handover for vehicle in motion to support continuous and seamless connection while roaming in the new PMIPv6 domain. In this paper we analytically evaluate our novel scheme to support inter-domain mobility for vehicle  roaming  between  two  PMIPv6  domains  by  using  Media  Independent  Handover (MIH) and Fully Qualified Domain Name (FQDN) to support the handover in addition to a continuous connection.

VANETs are one of the main next generation wireless networks which are envisaged to be an integration of homogeneous and heterogeneous wireless networks. The inter-networking of these wireless networks with the Internet will provide ubiquitous access to roaming network users. However, a seamless handover mechanism with negligible handover delay is required to maintain active connections during roaming across these networks. Several solutions, mainly involving host-based localized mobility management schemes, have been widely proposed to reduce handover delay among homogeneous and heterogeneous wireless networks. However, the handover delay remains high and unacceptable for delay-sensitive services such as real-time and multimedia services. Moreover, these services will be very common in next generation wireless networks. Unfortunately, these widely proposed host-based localized mobility management schemes involve the vehicle in mobility-related signaling hence effectively increasing the handover delay. Furthermore, these schemes do not properly address the advanced handover scenarios envisaged in future wireless networks. This paper, therefore, proposes a Logical Cross-Layer Optimization Block for VANET vertical mobility management framework utilizing cross-layer design, the IEEE 802.21 future standard, and the recently emerged network-based localized mobility management protocol, Proxy Mobile IPv6, to further reduce handover delay.

Nowadays, Grid Computing has been accepted as an infrastructure to perform parallel computing in distributed computational resources. Grid has users, resources, and an information service (IS). Resource broker service is one of the main services in grid to find resources, filter resources, allocate resources, etc. Resource selection is part of resource broker that is an important issue in a grid environment where a consumer and a service provider are distributed geographically. In this paper, we design and implement a new data mining -based Grid resource broker service for selection resources on grid environment. The role of this resource broker service is using learning method to find the best nodes according to the requirements of the job and the distributed computing resources on the Grid. The provided application can be executed on top of Globus Toolkit (GT) middleware. The results of experiments show a strong effect in improving resource finding cycle.

While Grid environment has developed increasingly, unfortunately the importance of fault tolerance has not been remarkable in Grid resource management. On the other hand, the cost of computing by grid is important because grid is an economy-based system. Most organizations intend to spend little on their own computations by grid. Therefore, using a better approach to resource scheduling to avoid fault is necessary. This paper presents a new approach on fault tolerance mechanisms for the resource scheduling on grid by using Case-Based Reasoning technique in a local fashion. This approach applies a specific structure in order to prepare fault tolerance between exécuter nodes to retain system in a safe state with minimum data transferring. Certainly, this algorithm increases fault tolerant confidence therefore, performance of grid will be high.

Computational Grid is enormous environments with heterogeneous resources and stable infrastructures among other Internet-based computing systems. However, the managing of resources in such systems has its special problems. Scheduler systems need to get last information about participant nodes from information centers for the purpose of firmly job scheduling. In this paper, we focus on online updating resource information centers with processed and provided data based on the assumed hierarchical model. A hybrid knowledge extraction method has been used to classifying grid nodes based on prediction of jobs' features. An affirmative point of this research is that scheduler systems don't waste extra time for getting up-to-date information of grid nodes. The experimental result shows the advantages of our approach compared to other conservative methods, especially due to its ability to predict the behavior of nodes based on comprehensive data tables on each node.

Since the Grid is a dynamic environment, the detection of available resources and prediction of resource availability in near future is important for resource scheduling. In a Grid environment, prediction and evaluation of resource availability is the prerequisite for a reasonable resource selection and good scheduling guarantee. There are many approaches for discovery and prediction of the resource availability that have some weaknesses (e.g., complexity time, predicting, using out of date data, etc). In this paper, we present a new method for detection of available resource based on online-announcer with no inquiry from Grid scheduler. We use a rough set analysis in each grid node to get some useful rules for predicting about node's behavior in the grid. The experiment results show that our proposed approach is fast algorithm and it applies effectively a reliable method to predict of proper resources for scheduling.

With the increasing complexity of dynamic and collaborative computing environments in Grid, access control has become a critical factor. Several approaches have been proposed in grid environment for scalable and efficient authorizations that are either VO-centric or Resource-centric. Reviewing different kinds of proposed authorization systems, we find out that VO-level and Resource-level authorization systems look at two different aspects of the grid authorization. Indeed, they complement each other, and can be implemented together to provide a holistic authorization solution. For this purpose, we propose a new access control framework which uses an extended two level RBAC model in Grid computing environments. By separating the administrations of users by VO level policies and mapping these policies to resources by resource or service providers, our scheme provides decentralized, autonomous, and fine-grained security management. The art of this approach is support of high flexibility in policy configuration, dynamically modifying authorization policies and reducing the cost of policy management.

In market-like grids, applying an economical method for providing fault-tolerant job scheduling is necessary. Since we have to pay cost for job execution in economic grids, consumers tend to execute their jobs on a grid with minimum cost and acceptable completion time. To do this, many approaches have been proposed, but they unilaterally consider either time/cost or consumer/provider profit. Based on current research, a new approach has been proposed; the approach is an optimized, fault-tolerant method for meta-scheduler that considers bilateral satisfaction for consumer/provider and a tolerable completion time. We suppose that, if one of the provider nodes fails, there would not be enough time to start a task on a new node from the beginning. The experimental results show a promising improvement in job scheduling with less computation cost, better fault-tolerance, and an acceptable completion time.

A market-based computational grid is made up of large sets of heterogeneous and geographically distributed resources that are gathered into virtual organizations for executing consumer's applications. One of the most important challenges in market-based grid systems is the management of grid users, which is called resource providers and consumers. The existing methods provide some alternative mechanisms for this problem, but they are not fully adequate. To address this problem, we propose an enhanced approach for adjusting price of grid resource using new effective parameters of microeconomic issue and also for prioritizing current jobs in the queue. This proposed approach is integrated with a cooperative method among local schedulers to accept jobs based on auction model. The results conclude that the inclusion of new parameters in price-adjusting affects the payment budget and job submission behavior of the schedulers. The evaluations of experimental results prove a remarkable performance of the proposed approach in diverse conditions and job workloads.

In market-based Grid systems, a main aim is to execute jobs with considered quality of service requirements based on user defined budget. Since grid has heterogonous resource with unpredictable faults, the user cost constraints and expected service requirements may not provided. Therefore, using a better approach to resource scheduling to reduce fault is necessary. This paper presents a predictive approach on fault tolerance mechanisms for faultless job scheduling on market-based grids. The Case-Based Reasoning technique has been used for selecting fault tolerant nodes. This approach applies a specific structure in order to prepare fault tolerance between provider nodes to retain system in a safe state with minimum data transferring. Certainly, this algorithm increases fault tolerant confidence therefore, performance of grid will be high.

With the growth of market-oriented grid and cloud computing systems, the need for efficient and cost effective job submission service in a job scheduling system is increasing rapidly. This paper proposes a flexible job submission service in local scheduling and a capable task submission and managing service with a flexible job queuing policy in provider nodes concerning jobs' priority and quality of service (QoS) requirements. The performance of proposed approach is compared to other algorithms based on the standard metrics. The results show that the proposed approach efficiently manages the arrival jobs in a market-oriented grids based on job's specifications and consumer's requirements via the efficient policy and methods for queuing jobs and accurate estimations for job submission.

Stability and durability requirement of the market-oriented Cloud computing environment is the continuous presence of consumers and providers. Naturally, when resource productivity and provider revenue are on an acceptable level, providers' satisfaction is positively influenced. In addition, quality of service parameters as time, cost and reliability have a direct influence on the satisfaction rate of consumers. The cloud provider service should obtain provider and consumer satisfaction to create and maintain stability; however, it faces with an important challenge. The resource provider service should consider contradictory criteria for selecting resources to implement the requests of consumers. In addition, the number of selectable resource samples is high in the extensive Cloud environment; i.e. Cloud resource provider service faces an NP-complete problem. In this paper, the resource selection and discovery service is presented using the concept of inflation phenomenon. Our proposed approach minimizes inflation rate as the main parameter of resource selection and maintains consumer and provider satisfaction. The conducted experiments show the efficiency rate of this service.

With the growth of market-oriented grid and cloud computing systems, the need for efficient and cost effective job submission service in a job scheduling system is increasing rapidly. This paper proposes a flexible job submission service in local scheduling and a capable task submission and managing service with a flexible job queuing policy in provider nodes concerning jobs' priority and quality of service (QoS) requirements. The performance of proposed approach is compared to other algorithms based on the standard metrics. The results show that the proposed approach efficiently manages the arrival jobs in a market-oriented grids based on job's specifications and consumer's requirements via the efficient policy and methods for queuing jobs and accurate estimations for job submission.

Wheat is the main food crop in Iran. There are many reasons that decrease the wheat production. Wheat pests are the main problem that affects wheat production. There are many different insects that attack wheat. In this research, we have concentrated on sunn pest (Eurygaster integriceps) and stripe rust as pervasive pests in the studied regions. This paper proposes a rule-based clustering algorithm to extract useful rules to predict the possible infections by the wheat pests and control them. We have used the limited data sets in three state of Iran (east Azerbaijan, west Azerbaijan, and Ardabil). The evaluation of proposed algorithm on our gathered data reveals more accurate compared with the crisp clustering methods and reduces the errors.

Nowadays, most universities and organizations use various computer systems, operating systems, mobile devices and databases with different infrastructure, hardware and software architectures. Many internet-based systems and advanced distributed environments have currently been developed in adapting to heterogonous systems. Cloud and grid computing are the new developed environments that present required services of users. In virtual education system, learners use different systems and facilities in various geographical locations. Therefore, evaluating the quality of education of learners is sophisticate. To this issue, we have developed a new approach for analyzing and extracting useful rules based on distributed heterogonous environments. For this research, we have implemented our proposed approach based on simulated grid computing environment. The obtained results confirm that the extracted rules based on distributed information can be useful to personalize education system for learners based on their characteristics and locations. This new architecture is powerful and rapid in comparison with centralized architectures.

In market-based Grid systems, a main aim is to execute jobs with considered quality of service requirements based on user defined budget. Since grid has heterogonous resource with unpredictable faults, the user cost constraints and expected service requirements may not provided. Therefore, using a better approach to resource scheduling to reduce fault is necessary. This paper presents a predictive approach on fault tolerance mechanisms for faultless job scheduling on market-based grids. The Case-Based Reasoning technique has been used for selecting fault tolerant nodes. This approach applies a specific structure in order to prepare fault tolerance between provider nodes to retain system in a safe state with minimum data transferring. Certainly, this algorithm increases fault tolerant confidence therefore, performance of grid will be high.