Nader Mohamed

The concept of cache has proven to be very beneficial in various domains. This paper introduces the concept of distributed cloud cache. It uses small caches available on servers or fog nodes over the Internet to reduce the load on the data centers. Dual-direction parallel transfer is used to improve download times of new released software, games, and movies from the release point to the clients.

Cyber-Physical Systems (CPS) are being developed to provide useful interactions between physical systems and environments and cyber world for a variety of applications. CPS are designed with a set of software and interconnected distributed hardware components that are linked with physical elements to provide advanced monitoring and control mechanisms geared towards enhancing the targeted physical system or environment. These components function seamlessly to offer specific functionalities that help enhance human lives, physical system operations and environments. While CPS can offer many smart enhancements for improving physical processes, the development of such complex systems composed of many distributed and heterogeneous components is extremely difficult. This is due to the many communication, computing, and networking challenges. Using an appropriate middleware that provides a framework to support developing and operating diverse CPS applications is a novel method to address these challenges. The availability of advanced middleware services and platforms can provide effective approaches for enhancing CPS application development processes as well as provide more robust environments for operating CPS applications. Such middleware can significantly reduce the time needed to design, build, test, and operate robust CPS applications. However, designing a common middleware platform for diverse types of CPS applications is not trivial. This paper investigates the middleware challenges for CPS, based on the different types of CPS applications being developed and their specific challenges. In addition, the paper discusses the current efforts of developing middleware platforms for CPS and the open research issues in the field.

The vehicle-to-vehicle (V2V) data transmissions in Vehicular Ad-hoc Networks (VANETs) have been applied in many areas including the Internet of Vehicles, mobile data offloading, and mobile crowdsensing. The V2V-based data delivery that is opposite to the direction of a vehicle is called a backward delivery against the traffic flow, and it is blocked by an existing problem: a traffic hole. Under the backward delivery with a traffic hole problem, there are no available vehicles that can move the data to its destination using the movement-assisted routing protocol; the data move in the direction opposite to that of the vehicle's motion. In this paper, we investigate backward data delivery under the traffic hole problem in order to provide more opportunities for V2V data transmissions. To mitigate the impact of the traffic hole on the backward data delivery, we propose an RSU-Assisted Backward Delivery scheme (RABD) which employs the roadside units (RSUs) as low-cost relays instead of traditional access points. RABD combines two methods of data delivery: one based on backward data forwarding among vehicles and another which is forwarded by the RSU. To reduce resource consumption, we investigate the single-copy scheme and consider the tradeoffs of both methods. Our extensional simulations verify the effectiveness of our proposed schemes.

UAVs, Unmanned Aerial Vehicles, have gained significant attention recently, due to the increasingly growing range of applications. Most UAVs use radio frequency transmission to communicate with the ground station to receive commands and send data. However, this model of communication restricts the user to being in specific locations and limits missions to narrow areas. This paper proposes a Cloud Computing (CC) integration where the UAVs become part of the cloud infrastructure and can be accessed ubiquitously. This concept is similar to the Internet of Things (IoT) where smart objects are connected to the Internet and are given unique identification. Moreover, to provide an appropriate way of communication, UAV resources are developed as web services. They provide their resources and services through a uniform interface using the RESTful HTTP architecture. This concept is relevant to the Web of Things (WoT) that provides smart objects with interfaces to be accessed through the World Wide Web (WWW). However, in UAVs, not only the web services are computational services but they are also physical elements affecting and affected by the real world environment.

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner.

Wireless sensor networks (WSNs) are used to monitor long linear structures such as pipelines, rivers, railroads, international borders, and high power transmission cables. In this case, a special type of WSN called linear wireless sensor network (LSN) is used. One of the main challenges of using LSNs is the reliability of the connections across the nodes. Faults in a few contiguous nodes may cause the creation of holes (segments where nodes on either end of them cannot reach each other) which will result in dividing the network into multiple disconnected segments. As a result, sensor nodes that are located between holes may not be able to deliver their sensed information which negatively affects the network's sensing coverage. In this paper, we provide an analysis of the different types of node faults in uniformly deployed LSNs and study their negative impact on the sensing coverage. We develop an analytical model to estimate the sensing coverage in uniformly deployed sensors LSNs in the presence of node faults. We verify the correctness of the developed model by conducting a number of simulation experiments to compare both calculated and simulated results under different network configurations and fault scenarios. In addition, we use this model to demonstrate three design applications that meet with specific performance requirements.

Wireless sensor networks (WSNs) can be used to monitor long linear structures such as pipelines, rivers, railroads, international borders, and high power transmission cables. In this case a special type of WSN called linear wireless sensor network (LSN) is used. One of the main challenges of using LSN is the reliability of the connections among the nodes. Faults in a few contiguous nodes may cause the creation of holes which will result in dividing the network into multiple disconnected segments. As a result, sensor nodes that are located between holes may not be able to deliver their sensed information which negatively affects the network's sensing coverage. Sensing robots can be used to overcome these faults and enhance the coverage. Sensing robots provide additional sensing coverage and restore the connectivity among disconnected segments. This paper develops a cost-effective design for robot-assisted fault-tolerant LSN. In this design the numbers of fixed sensor nodes and mobile sensing robots are determined such that the required reliability and sensing coverage levels are maintained while the total cost is minimized. The paper covers both uniformly and randomly deployed sensors LSNs.

Recently, most healthcare organizations focus their attention on reducing the cost of their supply chain management (SCM) by improving the decision making pertaining processes’ efficiencies. The availability of products through healthcare SCM is often a matter of life or death to the patient; therefore, trial and error approaches are not an option in this environment. Simulation and modeling (SM) has been presented as an alternative approach for supply chain managers in healthcare organizations to test solutions and to support decision making processes associated with various SCM problems. This paper presents and analyzes past SM efforts to support decision making in healthcare SCM and identifies the key challenges associated with healthcare SCM modeling. We also present and discuss emerging technologies to meet these challenges.

Summary: The Cloud relies heavily on resource replication to support the demands of the clients efficiently. Replicated Cloud services are distributed across large geographic areas and are accessible via the Internet. This paper describes MidCloud; an agent‐based middleware that provides Cloud clients with dynamic load balancing and fault tolerance mechanisms for effective utilization of replicated Cloud services and resources. MidCloud can be used to connect clients with multiple replicated Cloud services and provide fast and reliable service delivery from multiple replicas. Several approaches for load balancing and fault tolerance in distributed systems were introduced; however, they require prior knowledge of the environment's operating conditions and/or constant monitoring of these conditions at run time that allows the applications to adjust the load and redistribute the tasks when operational conditions change and when failures occur. These techniques work well when there is no high communication delay. Yet, this is not true in the Cloud, where data storage and computation servers are scattered all over the world and communication delays are usually very high. MidCloud deploys approaches to reduce the negative impact of high and dynamic delays on the Cloud servers and the Internet. The experimental results show the positive effects of using MidCloud to provide efficient load balancing and fault tolerance. Copyright © 2013 John Wiley & Sons, Ltd.