Bhaskar Prasad Rimal

A Taxonomy, Survey, and Issues of Cloud Computing Ecosystems

Cloud computing has emerged as a popular computing model to support processing of volumetric data using clusters of commodity computers. Nowadays, the computational world is opting for pay-for-use models. Hype and discussion aside, there remains no concrete definition of cloud computing. This chapter describes a comprehensive taxonomy for cloud computing architecture, aiming at a better understanding of the categories of applications that could benefit from cloudification and that will address the landscape of enterprise IT, management services, data governance, and many more. Then, this taxonomy is used to survey several cloud computing services such as Google, Force.com, and Amazon. The usages of taxonomy and survey results are not only to identify similarities and differences of the architectural approaches of cloud computing, but also to identify the areas requiring further research.

The tactile internet: vision, recent progress, and open challenges

The advent of commercially available remote-presence robots may be the precursor of an age of technological convergence, where important tasks of our everyday life will be increasingly done by robots. A very low roundtrip latency in conjunction with ultra-high reliability and essentially guaranteed availability for control communications has the potential to move todays mobile broadband experience into the new world of the Tactile Internet for a race with (rather than against) machines. To facilitate a better understanding of the Tactile Internet, this article first elaborates on the commonalities and subtle differences between the Tactile Internet and the Internet of Things and 5G vision. After briefly reviewing its anticipated impact on society and infrastructure requirements, we then provide an up-to-date survey of recent progress and enabling technologies proposed for the Tactile Internet. Given that scaling up research in the area of future wired and wireless access networks will be essential for the Tactile Internet, we pay particular attention to the latency and reliability performance gains of fiber-wireless (FiWi) enhanced LTE-Advanced heterogeneous networks and their role for emerging cloudlets, mobile-edge computing, and cloud robotics. Finally, we conclude by outlining remaining open challenges for the Tactile Internet.

Mobile Edge Computing Empowered Fiber-Wireless Access Networks in the 5G Era

The expected stringent requirements of future 5G networks such as ultra-low latency, user experience continuity, and high reliability will drive the need for highly localized services within RANs in close proximity to mobile subscribers. In light of this, the mobile edge computing (MEC) concept has emerged, which aims to unite telco, IT, and cloud computing to deliver cloud services directly from the network edge. To facilitate better understanding of MEC, this article first discusses its potential service scenarios and identifies design challenges of MEC-enabled networks. Given the importance of scaling up research in the area of network integration and convergence in support of MEC toward 5G, the article explores the possibilities of empowering integrated fiber-wireless (FiWi) access networks to offer MEC capabilities. More specifically, envisioned design scenarios of MEC over FiWi networks for typical RAN technologies (i.e., WLAN, 4G LTE, LTE-A HetNets) are investigated, accounting for both network architecture and enhanced resource management. The performance of MEC over Ethernet-based FiWi networks in terms of delay, response time efficiency, and battery life of edge devices is then analyzed. The obtained results demonstrate the feasibility and effectiveness of the proposed MEC over FiWi concept.

Mobile-edge computing vs. centralized cloud computing in fiber-wireless access networks

The advent of Internet of Things and 5G applications renders the need for integration of both centralized cloud computing and emerging mobile-edge computing (MEC) with existing network infrastructures to enhance storage, processing, and caching capabilities in not only centralized but also distributed fashions for supporting both delay-tolerant and mission-critical applications. This paper investigates performance gains of centralized cloud and MEC enabled integrated fiber-wireless (FiWi) access networks. A novel resource management scheme incorporating both centralized cloud and MEC offloading activities into the underlying FiWi dynamic bandwidth allocation process is proposed. An analytical framework is developed to model packet delay, response time efficiency, and gain-offload overhead ratio for both cloud and conventional broadband access traffic. The obtained results demonstrate the feasibility of implementing conventional cloud and MEC in FiWi access networks, while not affecting network performance of broadband access traffic.

Workflow Scheduling in Multi-Tenant Cloud Computing Environments

Multi-tenancy is one of the key features of cloud computing, which provides scalability and economic benefits to the end-users and service providers by sharing the same cloud platform and its underlying infrastructure with the isolation of shared network and compute resources. However, resource management in the context of multi-tenant cloud computing is becoming one of the most complex task due to the inherent heterogeneity and resource isolation. This paper proposes a novel cloud-based workflow scheduling (CWSA) policy for compute-intensive workflow applications in multi-tenant cloud computing environments, which helps minimize the overall workflow completion time, tardiness, cost of execution of the workflows, and utilize idle resources of cloud effectively. The proposed algorithm is compared with the state-of-the-art algorithms, i.e., First Come First Served (FCFS), EASY Backfilling, and Minimum Completion Time (MCT) scheduling policies to evaluate the performance. Further, a proof-of-concept experiment of real-world scientific workflow applications is performed to demonstrate the scalability of the CWSA, which verifies the effectiveness of the proposed solution. The simulation results show that the proposed scheduling policy improves the workflow performance and outperforms the aforementioned alternative scheduling policies under typical deployment scenarios.

Open Energy Market Strategies in Microgrids: A Stackelberg Game Approach Based on a Hybrid Multiobjective Evolutionary Algorithm

The emergence of microsources holds promise to reduce the carbon emissions and exploit more renewables in order to meet the worldwide growing electrical energy demands. However, there exist several challenges, such as optimizing the tradeoff between the use of renewable and nonrenewable energy sources, to leverage affordable electric power while minimizing carbon emissions. Game theoretic approaches have been widely used in various scientific domains and have recently also increasingly been used in smart grids, whereby evolutionary paradigms have been widely deployed as a popular heuristic search method to solve and optimize complex real-life scientific problems. A promising approach is the development of such evolutionary algorithms and game theoretic approaches in the context of open energy markets. In this paper, we develop an analytic model of a multileader and multifollower Stackelberg game approach and propose a bi-level hybrid multiobjective evolutionary algorithm to find optimal strategies that maximize the profit of utilities, and minimize carbon emissions in an open energy market among interconnected microsources.

Invited paper: The audacity of fiber-wireless (FiWi) networks: revisited for clouds and cloudlets

There is a growing awareness among industry players of reaping the benefits of mobile-cloud convergence by extending todays unmodified cloud to a decentralized two-level cloud-cloudlet architecture based on emerging mobile-edge computing (MEC) capabilities. In light of future 5G mobile networks moving toward decentralization based on cloudlets, intelligent base stations, and MEC, the inherent distributed processing and storage capabilities of radio-and-fiber (R&F) networks may be exploited for new applications, e.g., cognitive assistance, augmented reality, or cloud robotics. In this paper, we first revisit fiber-wireless (FiWi) networks in the context of conventional clouds and emerging cloudlets, thereby highlighting the limitations of conventional radio-overfiber (RoF) networks such as China Mobiles centralized cloud radio access network (C-RAN) to meet the aforementioned trends. Furthermore, we pay close attention to the specific design challenges of data center networks and revisit our switchless arrayed waveguide grating (AWG) based network with efficient support of east-west flows and enhanced scalability.

Machine-to-machine communications over FiWi enhanced LTE networks : A power-saving framework and end-to-end performance

To cope with the unprecedented acceleration of machine-to-machine (M2M) services over cellular networks, this paper envisions a highly converged network architecture based on the integration of high-capacity and reliable Ethernet fiber-wireless (FiWi) access networks with flexible and cost-effective 4G long term evolution (LTE) technology to support M2M connectivity in an end-to-end fashion, i.e., from air interface to transport (backhaul) network. In such emerging architecture, energy efficiency must be addressed in a comprehensive way, in which both wireless front-end and optical backhaul segments are considered at the same time to maximize the battery life of battery-constrained M2M devices as well as reduce operational expenditures for network operators, while maintaining acceptable network performance. Toward this end, an end-to-end power-saving framework is introduced in this paper that devises a timeout driven discontinuous reception (DRX) mechanism for LTE-enabled M2M devices and a polling-based power-saving mechanism for optical network units (ONUs) to improve the overall energy efficiency. End-to-end performance in terms of energy saving and packet delay is analytically modeled based on a semi-Markov process for the front-end and an M/G/1 queue for the backhaul. The obtained results indicate that the device battery life is significantly prolonged by extending the DRX cycle, whereas the backhaul energy consumption is minimized by incorporating the ONU power-saving modes into the dynamic bandwidth allocation process of the optical backhaul.

Multi-objective pricing game among interconnected smart microgrids

Future power grids are expected to be a combination of interconnected microgrids leveraging solar, wind, and plugin electrical vehicles (PEVs). Due to the intermittent nature of renewable energy sources, smart microgrids may not be able to consistently meet the demands of all the prosumers connected to them. Therefore, the necessity of power trading algorithms is becoming increasingly important. Recently, game theory has emerged as one of the analytical frameworks to deal with the aforementioned issues in the context of smart grids. In this paper, we develop a pricing mechanism for interconnected smart microgrids based on potential game theory. We develop a mathematical model and simulation engine to study the anticipated benefits of an open market, where multiple suppliers and multiple prosumers coexist. We demonstrate that our model captures the energy losses, real-time cost, and production to optimize the overall losses and total production costs.

Cloudlet Enhanced Fiber-Wireless Access Networks for Mobile-Edge Computing

This paper proposes to enhance capacity-centric fiber-wireless (FiWi) broadband access networks based on data-centric Ethernet technologies with computation- and storage-centric cloudlets to provide reliable cloud services at the edge of FiWi networks and thereby realize the vision of mobile-edge computing (MEC). To reduce offload delay and prolong battery life of edge devices, a novel cloudlet-aware resource management scheme is proposed that incorporates offloading activities into the underlying FiWi dynamic bandwidth allocation process. The whole system is designed in two time division multiple access layers to enhance the network performance. To allow for the efficient coexistence of FiWi and MEC traffic, the offloaded traffic is scheduled outside the FiWi transmission slots. To thoroughly study the scheme’s performance, a comprehensive analytical framework is developed that covers a rich set of performance metrics, including packet delay of both FiWi and MEC traffic, response time efficiency, offload gain-overhead ratio, energy efficiency, and battery life. Analytical results demonstrate the feasibility and effectiveness of the cloudlet-enhanced FiWi networks for MEC by employing the proposed solution. Further, we develop an experimental testbed to validate the accuracy of our analytical model via real-world measurements.