Mobile edge computing (MEC) is a novel computing paradigm that sinks the computing capacity of cloud servers into edge nodes to reduce network latency. By caching the popular content at small base station (SBS) can re...
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ISBN:
(数字)9781665486439
ISBN:
(纸本)9781665486439
Mobile edge computing (MEC) is a novel computing paradigm that sinks the computing capacity of cloud servers into edge nodes to reduce network latency. By caching the popular content at small base station (SBS) can reduce the heavy backhaul load and the content retransmission in MEC. However, the dynamic and time-varying of the content requests may increase the network cost. In this paper, we study a distributed edge caching optimization problem in MEC scenario with the spatiotemporal requirements. The considered cache control is described as a stochastic differential game (SDG) in which each SBS defines a caching strategy to reduce the cost in terms of the service delay and backhaul link load. To reduce the computational complexity, the original problem can be transformed into a mean field game (MFG). We propose a caching iterative control algorithm that decouples the information interactions between the general SBS and others with the mean field distribution. In addition, we obtain the optimal caching strategy which achieves the existence and uniqueness of the mean field equilibrium (MFE). Simulation results demonstrate that our proposed algorithm can reduce more storage space and total cost compared to the Kim's approach.
In this paper, we propose a new service orchestration approach for in-network fully distributed dynamic compute composition with limited involvement from the consumer and no centralized coordinator. The service is com...
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ISBN:
(纸本)9798350311143
In this paper, we propose a new service orchestration approach for in-network fully distributed dynamic compute composition with limited involvement from the consumer and no centralized coordinator. The service is composed fully inside the network including assembling data and software, and compute node selection, leveraging standardized NDN functionalities. The use of the proposed approach will enable smooth support of dynamic compute services over wireless/mobile edge and edge/fog NDN-based systems, where the use of conventional IP approach faces fundamental difficulties related to dynamic allocation of IP addresses. We will also outline extensions of the proposed approach for streaming data, function chaining and re-use of partially computed results. Our numerical results show that the proposed method improves service reliability at the edge by increasing the Interest satisfaction by 5-10 times depending on the considered deployment, network topology, and resources.
A Short Time Fourier Transform (STFT)-based approach is introduced to enhance power quality in distributed energy integration with low-voltage substations. This method utilizes STFT to segment signals with a time-freq...
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Drawing from four years of international research, the Ancestral Paradigm is a way to question the ontological, epistemological and axiological foundations of Computer Science (CS). This paradigm allows us to shift aw...
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ISBN:
(纸本)9798350328332;9798350328325
Drawing from four years of international research, the Ancestral Paradigm is a way to question the ontological, epistemological and axiological foundations of Computer Science (CS). This paradigm allows us to shift away from the ethos of: a. settler colonialism;b. CS as a child of the military;and c. harmful environmental extraction practices;towards a praxis of life-sustaining CS. Centering Ancestral Paradigms into the core knowledge of CS honors historically marginalized knowledge systems that imagine new ways of producing CS. The authors will share the core values of the Ancestral Paradigm as a BPC strategy to decolonize computing.
Prefix Scan is a versatile collective used in several classes of algorithms including sorting, lexical analysis, graph analytics, and regex matching. It is also a powerful tool to perform tree operations and load bala...
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ISBN:
(纸本)9781665494236
Prefix Scan is a versatile collective used in several classes of algorithms including sorting, lexical analysis, graph analytics, and regex matching. It is also a powerful tool to perform tree operations and load balancing. However, host-based Prefix Scan implementations incur high latency, large network traffic and poor scalability on large distributedsystems. We explore in-network computation to accelerate Prefix Scan, using switches with data aggregation capabilities. We discuss the fundamental challenges associated with offloading Prefix Scan onto a network, and resolve them with innovations in dataflow topology and embedding methodology. We implement the proposed approach on the Intel PIUMA system. To the best of our knowledge, this is the first realization of a Prefix Scan offloading onto network switches. Our in-network Prefix Scan is highly scalable with less than 5 mu s latency on 16K PIUMA nodes and 6x lower latency than the host-based Prefix Scan. The performance benefits directly translate to improved workload scalability, as we demonstrate using a key bioinformatics application called Sequence Alignment.
P2P Botnet is famous for the resilience against termination. However, its dependence on Neighbor List (NL) makes it susceptible to infiltration and poison, also leading to a dearth of adequate protection of Botmaster&...
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This paper investigates the distributed DC optimal power flow (OPF) problem with carbon emission trading. In recent years, the alternating direction method of multipliers (ADMM) has been used to solve the optimal powe...
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On a daily basis, data centers process huge volumes of data backed by the proliferation of inexpensive hard disks. Data stored in these disks serve a range of critical functional needs from financial, and healthcare t...
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ISBN:
(纸本)9798350322811
On a daily basis, data centers process huge volumes of data backed by the proliferation of inexpensive hard disks. Data stored in these disks serve a range of critical functional needs from financial, and healthcare to aerospace. As such, premature disk failure and consequent loss of data can be catastrophic. To mitigate the risk of failures, cloud storage providers perform condition-based monitoring and replace hard disks before they fail. By estimating the remaining useful life of hard disk drives, one can predict the time-to-failure of a particular device and replace it at the right time, ensuring maximum utilization whilst reducing operational costs. In this work, large-scale predictive analyses are performed using severely skewed health statistics data by incorporating customized feature engineering and a suite of sequence learners. Past work suggests using LSTMs as an excellent approach to predicting remaining useful life. To this end, we present an encoder-decoder LSTM model where the context gained from understanding health statistics sequences aid in predicting an output sequence of the number of days remaining before a disk potentially fails. The models developed in this work are trained and tested across an exhaustive set of all of the 10 years of S.M.A.R.T. health data in circulation from Backblaze and on a wide variety of disk instances. It closes the knowledge gap on what full-scale training achieves on thousands of devices and advances the state-of-the-art by providing tangible metrics for evaluation and generalization for practitioners looking to extend their workflow to all years of health data in circulation across disk manufacturers. The encoder-decoder LSTM posted an RMSE of 0.83 during training and 0.86 during testing over the exhaustive 10-year data while being able to generalize competitively over other drives from the Seagate family.
Detecting handwritten Punjabi alphabets (PbAD) presents significant challenges for text detection systems due to the similarity among many characters and their complex curves and edges. Existing automatic detection sy...
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The research work introduces the concept of a Doctor Appointment Website, a digital platform designed to optimize the process of scheduling and managing medical appointments. The platform allows patients to search for...
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