Recent developments and technological advancements in wireless communication, MicroElectroMechanical Systems (MEMS) technology and integrated circuits has enabled low-power, intelligent, miniaturized, invasive/non-invasive micro and nano-technology sensor nodes strategically placed in or around the human body to be used in various applications, such as personal health monitoring. This exciting new area of research is called Wireless Body Area Networks (WBANs) and leverages the emerging IEEE 802.15.6 and IEEE 802.15.4j standards, specifically standardized for medical WBANs. The aim of WBANs is to simplify and improve speed, accuracy, and reliability of communication of sensors/actuators within, on, and in the immediate proximity of a human body. The vast scope of challenges associated with WBANs has led to numerous publications. In this paper, we survey the current state-of-art of WBANs based on the latest standards and publications. Open issues and challenges within each area are also explored as a source of inspiration towards future developments in WBANs.

Wireless Body Area Networks: A Survey

https://titania.ctie.monash.edu/papers/vhd-survey-comp-networks-2010.pdf

A survey of vertical handover decision algorithms in Fourth Generation heterogeneous wireless networks

Connected Vehicle Technology (CVT) requires wireless data transmission between vehicles (V2V), and vehicle-to-infrastructure (V2I). Evaluating the performance of different network options for V2V and V2I communication that ensure optimal utilization of resources is a prerequisite when designing and developing robust wireless networks for CVT applications. Though dedicated short range communication (DSRC) has been considered as the primary communication option for CVT safety applications, the use of other wireless technologies (e.g., Wi-Fi, LTE, WiMAX) allow longer range communications and throughput requirements that could not be supported by DSRC alone. Further, the use of other wireless technology potentially reduces the need for costly DSRC infrastructure. In this research, the authors evaluated the performance of Het-Net consisting of Wi-Fi, DSRC and LTE technologies for V2V and V2I communications. An application layer handoff method was developed to enable Het-Net communication for two CVT applications: traffic data collection, and forward collision warning. The handoff method ensures the optimal utilization of available communication options (i.e., eliminate the need of using multiple communication options at the same time) and corresponding backhaul communication infrastructure depending on the connected vehicle application requirements. Field studies conducted in this research demonstrated that the use of Het-Net broadened the range and coverage of V2V and V2I communications. The use of the application layer handoff technique to maintain seamless connectivity for CVT applications was also successfully demonstrated and can be adopted in future Het-Net supported connected vehicle applications. A long handoff time was observed when the application switches from LTE to Wi-Fi. The delay is largely due to the time required to activate the 802.11 link and the time required for the vehicle to associate with the RSU (i.e., access point). Modifying the application to implement a soft handoff where a new network is seamlessly connected before breaking from the existing network can greatly reduce (or eliminate) the interruption of network service observed by the application. However, the use of a Het-Net did not compromise the performance of the traffic data collection application as this application does not require very low latency, unlike connected vehicle safety applications. Field tests revealed that the handoff between networks in Het-Net required several seconds (i.e., higher than 200 ms required for safety applications). Thus, Het-Net could not be used to support safety applications that require communication latency less than 200 ms. However, Het-Net could provide additional/supplementary connectivity for safety applications to warn vehicles upstream to take proactive actions to avoid problem locations. To validate and establish the findings from field tests that included a limited number of connected vehicles, ns-3 simulation experiments with a larger number of connected vehicles were conducted involving a DSRC and LTE Het-Net scenario. The latency and packet delivery error trend obtained from ns-3 simulation were found to be similar to the field experiment results.

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless network – Performance evaluation

For task-scheduling problems in cloud computing, a multi-objective optimization method is proposed here. First, with an aim toward the biodiversity of resources and tasks in cloud computing, we propose a resource cost model that defines the demand of tasks on resources with more details. This model reflects the relationship between the user’s resource costs and the budget costs. A multi-objective optimization scheduling method has been proposed based on this resource cost model. This method considers the makespan and the user’s budget costs as constraints of the optimization problem, achieving multi-objective optimization of both performance and cost. An improved ant colony algorithm has been proposed to solve this problem. Two constraint functions were used to evaluate and provide feedback regarding the performance and budget cost. These two constraint functions made the algorithm adjust the quality of the solution in a timely manner based on feedback in order to achieve the optimal solution. Some simulation experiments were designed to evaluate this method’s performance using four metrics: 1) the makespan; 2) cost; 3) deadline violation rate; and 4) resource utilization. Experimental results show that based on these four metrics, a multi-objective optimization method is better than other similar methods, especially as it increased 56.6% in the best case scenario.

A Multi-Objective Optimization Scheduling Method Based on the Ant Colony Algorithm in Cloud Computing

Over the years, programming languages have grown more powerful, but correspondingly more complex; and while that complexity is fine and appropriate for professional programmers, it hinders and discourages beginning Computer Science students.

Python: the tutorial

There are currently a large variety of wireless access networks, including the emerging vehicular ad hoc networks (VANETs). A large variety of applications utilizing these networks will demand features such as real-time, high-availability, and even instantaneous high-bandwidth in some cases. Therefore, it is imperative for network service providers to make the best possible use of the combined resources of available heterogeneous networks (wireless area networks (WLANs), Universal Mobile Telecommunications Systems, VANETs, Worldwide Interoperability for Microwave Access (WiMAX), etc.) for connection support. When connections need to migrate between heterogeneous networks for performance and high-availability reasons, seamless vertical handoff (VHO) is a necessary first step. In the near future, vehicular and other mobile applications will be expected to have seamless VHO between heterogeneous access networks. With regard to VHO performance, there is a critical need to develop algorithms for connection management and optimal resource allocation for seamless mobility. In this paper, we develop a VHO decision algorithm that enables a wireless access network to not only balance the overall load among all attachment points (e.g., base stations and access points) but also maximize the collective battery lifetime of mobile nodes (MNs). In addition, when ad hoc mode is applied to 3/4G wireless data networks, VANETs, and IEEE 802.11 WLANs for a more seamless integration of heterogeneous wireless networks, we devise a route-selection algorithm for forwarding data packets to the most appropriate attachment point to maximize collective battery lifetime and maintain load balancing. Results based on a detailed performance evaluation study are also presented here to demonstrate the efficacy of the proposed algorithms.

/pdf/vertical-handoff-decision-algorithms-for-providing-optimized-4ejt0u1x2b.pdf

Vertical Handoff Decision Algorithms for Providing Optimized Performance in Heterogeneous Wireless Networks

Internet of Vehicles (IoV) has emerged as a key component of smart cities. Connected vehicles are increasingly processing real-time data to respond immediately to user requests. However, the data must be sent to a remote cloud for processing. To resolve this issue, vehicular fog computing (VFC) has emerged as a promising paradigm that improves the quality of computation experiences for vehicles by offloading computation tasks from the cloud to network edges. Nevertheless, due to the resource restrictions of fog computing, only a limited number of vehicles are able to use it while it is still challenging to provide real-time responses for vehicular applications, such as traffic and accident warnings in the highly dynamic IoV environment. Therefore, in this article, we formulate the problem of allocating the limited fog resources to vehicular applications such that the service latency is minimized, by utilizing parked vehicles. We then propose a heuristic algorithm to efficiently find the solutions of the problem formulation. In addition, the proposed algorithm is combined with reinforcement learning to make more efficient resource allocation decisions, leveraging the vehicles’ movement and parking status collected from the smart environment of the city. Our simulation results show that our VFC resource allocation algorithm can achieve higher service satisfaction compared to conventional resource allocation algorithms.

Resource Allocation for Vehicular Fog Computing Using Reinforcement Learning Combined With Heuristic Information

The development of telemonitoring via wireless body area networks (WBANs) is an evolving direction in personalized medicine and home-based mobile health. A WBAN consists of small, intelligent medical sensors which collect physiological parameters such as electrocardiogram, electroencephalography, and blood pressure. The recorded physiological signals are sent to a coordinator via wireless technologies, and are then transmitted to a healthcare monitoring center. One of the most widely used wireless technologies in WBANs is ZigBee because it is targeted at applications that require a low data rate and long battery life. However, ZigBee-based WBANs face severe interference problems in the presence of WiFi networks. This problem is caused by the fact that most ZigBee channels overlap with WiFi channels, severely affecting the ability of healthcare monitoring systems to guarantee reliable delivery of physiological signals. To solve this problem, we have developed an algorithm that controls the load in WiFi networks to guarantee the delay requirement for physiological signals, especially for emergency messages, in environments with coexistence of ZigBee-based WBAN and WiFi. Since WiFi applications generate traffic with different delay requirements, we focus only on WiFi traffic that does not have stringent timing requirements. In this paper, therefore, we propose an adaptive load control algorithm for ZigBee-based WBAN/WiFi coexistence environments, with the aim of guaranteeing that the delay experienced by ZigBee sensors does not exceed a maximally tolerable period of time. Simulation results show that our proposed algorithm guarantees the delay performance of ZigBee-based WBANs by mitigating the effects of WiFi interference in various scenarios.

Coexistence of ZigBee-Based WBAN and WiFi for Health Telemonitoring Systems

In IEEE 802.11 standard, the backoff parameters of its collision avoidance mechanism can be very inefficient and hence, the network becomes far from its optimal behavior. There have been several mechanisms to tune the Contention Window (CW) with the aim to achieve the optimal throughput in the IEEE 802.11 WLAN, however, the mechanisms do not specifically address a proper setting of the backoff parameters under non-saturated conditions. Noting that typical 802.11 networks are usually non-saturated, in this paper, we analytically derive the CW sizes that maximize the WLAN system throughput under both saturated and non-saturated conditions. Then, using the CW sizes derived, we propose a distributed algorithm that enables each station to dynamically adapt its CW according to the channel congestion status. The performance of the proposed algorithm is investigated through simulation. Simulation results indicate that our proposed backoff algorithm provides a remarkable performance improvement in terms of the delay experienced by a packet in the MAC layer, while maintaining an optimal throughput close to the theoretical throughput limit of the IEEE 802.11 Distributed Coordination Function (DCF) access scheme.

Channel Condition Based Contention Window Adaptation in IEEE 802.11 WLANs

Cloud computing is computing in which large groups of remote servers are networked to allow centralized data storage and on-line access to computer services. Cloud computing providers install and operate application software in the cloud through Software as a Service (SaaS) model. Cloud users access the software and utilizes the services by cloning tasks onto multiple virtual machines (VMs). In recent years, offering high-performance computing capacity reminds cloud providers to utilize resources fully due to limitation of resource. Enhancing resource utilization is also essential for achieving cost effectiveness. In addition, SaaS applications support various services such as email, FTP, and multimedia services with different delay requirement. Among these application multimedia service has relatively low delay requirements. Therefore, in this paper, we propose a scheduling algorithm to enhance both deadline guarantee and resource utilization. We modified the conservative backfilling algorithm by utilizing the earliest deadline first (EDF) algorithm and the largest weight first (LWF) algorithm. The proposed algorithm first score all the jobs arrived at the data center(DC) and sort the jobs in ascending order to serve high priority job first. The proposed algorithm then select the largest possible backfill job as guaranteeing deadline. Simulation results show that the proposed algorithm significantly improve the performance in terms of resource utilization and deadline guarantee.

SuKyoung Lee

Papers

Vertical Handoff Decision Algorithms for Providing Optimized Performance in Heterogeneous Wireless Networks

Resource Allocation for Vehicular Fog Computing Using Reinforcement Learning Combined With Heuristic Information

Coexistence of ZigBee-Based WBAN and WiFi for Health Telemonitoring Systems

Channel Condition Based Contention Window Adaptation in IEEE 802.11 WLANs

Deadline-guaranteed scheduling algorithm with improved resource utilization for cloud computing