Pradipta De

Bio: Pradipta De is an academic researcher from Georgia Southern University. The author has contributed to research in topics: Wireless network & Virtual machine. The author has an hindex of 19, co-authored 105 publications receiving 1821 citations. Previous affiliations of Pradipta De include Stony Brook University & State University of New York System.

Server workload analysis for power minimization using consolidation

Abstract: Server consolidation has emerged as a promising technique to reduce the energy costs of a data center. In this work, we present the first detailed analysis of an enterprise server workload from the perspective of finding characteristics for consolidation. We observe significant potential for power savings if consolidation is performed using off-peak values for application demand. However, these savings come up with associated risks due to consolidation, particularly when the correlation between applications is not considered. We also investigate the stability in utilization trends for low-risk consolidation. Using the insights from the workload analysis, two new consolidation methods are designed that achieve significant power savings, while containing the performance risk of consolidation. We present an implementation of the methodologies in a consolidation planning tool and provide a comprehensive evaluation study of the proposed methodologies.

A Survey of Fingerprint-Based Outdoor Localization

Abstract: A growing number of sensors on smart mobile devices has led to rapid development of various mobile applications using location-based or context-aware services. Typically, outdoor localization techniques have relied on GPS or on cellular infrastructure support. While GPS gives high positioning accuracy, it can quickly deplete the battery on the device. On the other hand, base station based localization has low accuracy. In search of alternative techniques for outdoor localization, several approaches have explored the use of data gathered from other available sensors, like accelerometer, microphone, compass, and even daily patterns of usage, to identify unique signatures that can locate a device. Signatures, or fingerprints of an area, are hidden cues existing around a user's environment. However, under different operating scenarios, fingerprint-based localization techniques have variable performance in terms of accuracy, latency of detection, battery usage. The main contribution of this survey is to present a classification of existing fingerprint-based localization approaches which intelligently sense and match different clues from the environment for location identification. We describe how each fingerprinting technique works, followed by a review of the merits and demerits of the systems built based on these techniques. We conclude by identifying several improvements and application domain for fingerprinting based localization.

MiNT: a miniaturized network testbed for mobile wireless research

Abstract: Most mobile wireless networking research today relies on simulations. However, fidelity of simulation results has always been a concern, especially when the protocols being studied are affected by the propagation and interference characteristics of the radio channels. Inherent difficulty in faithfully modeling the wireless channel characteristics has encouraged several researchers to build wireless network testbeds. A full-fledged wireless testbed is spread over a large physical space because of the wide coverage area of radio signals. This makes a large-scale testbed difficult and expensive to set up, configure, and manage. This paper describes a miniaturized 802.11b-based, multi-hop wireless network testbed called MiNT. MiNT occupies a significantly small space, and dramatically reduces the efforts required in setting up a multi-hop wireless network used for wireless application/protocol testing and evaluation. MiNT is also a hybrid simulation platform that can execute ns-2 simulation scripts with the link, MAC and physical layer in the simulator replaced by real hardware. We demonstrate the fidelity of MiNT by comparing experimental results on it with similar experiments conducted on a non-miniaturized testbed. We also compare the results of experiments conducted using hybrid simulation on MiNT with those obtained using pure simulation. Finally, using a case study we show the usefulness of MiNT in wireless application testing and evaluation.

MiNT-m: an autonomous mobile wireless experimentation platform

Abstract: Limited fidelity of software-based wireless network simulations has prompted many researchers to build testbeds for developing and evaluating their wireless protocols and mobile applications. Since most testbeds are tailored to the needs of specific research projects, they cannot be easily reused for other research projects that may have different requirements on physical topology, radio channel characteristics or mobility pattern. In this paper, we describe the design, implementation and evaluation of MiNT-m, an experimentation platform devised specifically to support arbitrary experiments for mobile multi-hop wireless network protocols. In addition to inheriting the miniaturization feature from its predecessor MiNT [9], MiNT-m enables flexible testbed reconfiguration on an experiment-by-experiment basis by putting each testbed node on a centrally controlled untethered mobile robot. To support mobility and reconfiguration of testbed nodes, MiNT-m includes a scalable mobile robot navigation control subsystem, which in turn consists of a vision-based robot positioning module and a collision avoidance-based trajectory planning module. Further, MiNT-m provides a comprehensive network/experiment management subsystem that affords a user full interactive control over the testbed as well as real-time visualization of the testbed activities. Finally, because MiNT-m is designed to be a shared research infrastructure that supports 24x7 operation, it incorporates a novel automatic battery recharging capability that enables testbed robots to operate without human intervention for weeks.

Next Generation 5G Wireless Networks: A Comprehensive Survey

Abstract: The vision of next generation 5G wireless communications lies in providing very high data rates (typically of Gbps order), extremely low latency, manifold increase in base station capacity, and significant improvement in users’ perceived quality of service (QoS), compared to current 4G LTE networks. Ever increasing proliferation of smart devices, introduction of new emerging multimedia applications, together with an exponential rise in wireless data (multimedia) demand and usage is already creating a significant burden on existing cellular networks. 5G wireless systems, with improved data rates, capacity, latency, and QoS are expected to be the panacea of most of the current cellular networks’ problems. In this survey, we make an exhaustive review of wireless evolution toward 5G networks. We first discuss the new architectural changes associated with the radio access network (RAN) design, including air interfaces, smart antennas, cloud and heterogeneous RAN. Subsequently, we make an in-depth survey of underlying novel mm-wave physical layer technologies, encompassing new channel model estimation, directional antenna design, beamforming algorithms, and massive MIMO technologies. Next, the details of MAC layer protocols and multiplexing schemes needed to efficiently support this new physical layer are discussed. We also look into the killer applications, considered as the major driving force behind 5G. In order to understand the improved user experience, we provide highlights of new QoS, QoE, and SON features associated with the 5G evolution. For alleviating the increased network energy consumption and operating expenditure, we make a detail review on energy awareness and cost efficiency. As understanding the current status of 5G implementation is important for its eventual commercialization, we also discuss relevant field trials, drive tests, and simulation experiments. Finally, we point out major existing research issues and identify possible future research directions.

Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in Cloud data centers

Abstract: The rapid growth in demand for computational power driven by modern service applications combined with the shift to the Cloud computing model have led to the establishment of large-scale virtualized data centers. Such data centers consume enormous amounts of electrical energy resulting in high operating costs and carbon dioxide emissions. Dynamic consolidation of virtual machines (VMs) using live migration and switching idle nodes to the sleep mode allows Cloud providers to optimize resource usage and reduce energy consumption. However, the obligation of providing high quality of service to customers leads to the necessity in dealing with the energy-performance trade-off, as aggressive consolidation may lead to performance degradation. Because of the variability of workloads experienced by modern applications, the VM placement should be optimized continuously in an online manner. To understand the implications of the online nature of the problem, we conduct a competitive analysis and prove competitive ratios of optimal online deterministic algorithms for the single VM migration and dynamic VM consolidation problems. Furthermore, we propose novel adaptive heuristics for dynamic consolidation of VMs based on an analysis of historical data from the resource usage by VMs. The proposed algorithms significantly reduce energy consumption, while ensuring a high level of adherence to the service level agreement. We validate the high efficiency of the proposed algorithms by extensive simulations using real-world workload traces from more than a thousand PlanetLab VMs. Copyright © 2011 John Wiley & Sons, Ltd.

Recent Advances in Indoor Localization: A Survey on Theoretical Approaches and Applications

Abstract: The availability of location information has become a key factor in today's communications systems allowing location based services. In outdoor scenarios, the mobile terminal position is obtained with high accuracy thanks to the global positioning system (GPS) or to the standalone cellular systems. However, the main problem of GPS and cellular systems resides in the indoor environment and in scenarios with deep shadowing effects where the satellite or cellular signals are broken. In this paper, we survey different technologies and methodologies for indoor and outdoor localization with an emphasis on indoor methodologies and concepts. Additionally, we discuss in this review different localization-based applications, where the location information is critical to estimate. Finally, a comprehensive discussion of the challenges in terms of accuracy, cost, complexity, security, scalability, etc. is given. The aim of this survey is to provide a comprehensive overview of existing efforts as well as auspicious and anticipated dimensions for future work in indoor localization techniques and applications.

A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions

Abstract: The fifth generation (5G) wireless network technology is to be standardized by 2020, where main goals are to improve capacity, reliability, and energy efficiency, while reducing latency and massively increasing connection density. An integral part of 5G is the capability to transmit touch perception type real-time communication empowered by applicable robotics and haptics equipment at the network edge. In this regard, we need drastic changes in network architecture including core and radio access network (RAN) for achieving end-to-end latency on the order of 1 ms. In this paper, we present a detailed survey on the emerging technologies to achieve low latency communications considering three different solution domains: 1) RAN; 2) core network; and 3) caching. We also present a general overview of major 5G cellular network elements such as software defined network, network function virtualization, caching, and mobile edge computing capable of meeting latency and other 5G requirements.

Resource Management in Clouds: Survey and Research Challenges

Abstract: Resource management in a cloud environment is a hard problem, due to: the scale of modern data centers; the heterogeneity of resource types and their interdependencies; the variability and unpredictability of the load; as well as the range of objectives of the different actors in a cloud ecosystem. Consequently, both academia and industry began significant research efforts in this area. In this paper, we survey the recent literature, covering 250+ publications, and highlighting key results. We outline a conceptual framework for cloud resource management and use it to structure the state-of-the-art review. Based on our analysis, we identify five challenges for future investigation. These relate to: providing predictable performance for cloud-hosted applications; achieving global manageability for cloud systems; engineering scalable resource management systems; understanding economic behavior and cloud pricing; and developing solutions for the mobile cloud paradigm .