9,718 research outputs found
Learning and Management for Internet-of-Things: Accounting for Adaptivity and Scalability
Internet-of-Things (IoT) envisions an intelligent infrastructure of networked
smart devices offering task-specific monitoring and control services. The
unique features of IoT include extreme heterogeneity, massive number of
devices, and unpredictable dynamics partially due to human interaction. These
call for foundational innovations in network design and management. Ideally, it
should allow efficient adaptation to changing environments, and low-cost
implementation scalable to massive number of devices, subject to stringent
latency constraints. To this end, the overarching goal of this paper is to
outline a unified framework for online learning and management policies in IoT
through joint advances in communication, networking, learning, and
optimization. From the network architecture vantage point, the unified
framework leverages a promising fog architecture that enables smart devices to
have proximity access to cloud functionalities at the network edge, along the
cloud-to-things continuum. From the algorithmic perspective, key innovations
target online approaches adaptive to different degrees of nonstationarity in
IoT dynamics, and their scalable model-free implementation under limited
feedback that motivates blind or bandit approaches. The proposed framework
aspires to offer a stepping stone that leads to systematic designs and analysis
of task-specific learning and management schemes for IoT, along with a host of
new research directions to build on.Comment: Submitted on June 15 to Proceeding of IEEE Special Issue on Adaptive
and Scalable Communication Network
Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud
With the advent of cloud computing, organizations are nowadays able to react
rapidly to changing demands for computational resources. Not only individual
applications can be hosted on virtual cloud infrastructures, but also complete
business processes. This allows the realization of so-called elastic processes,
i.e., processes which are carried out using elastic cloud resources. Despite
the manifold benefits of elastic processes, there is still a lack of solutions
supporting them.
In this paper, we identify the state of the art of elastic Business Process
Management with a focus on infrastructural challenges. We conceptualize an
architecture for an elastic Business Process Management System and discuss
existing work on scheduling, resource allocation, monitoring, decentralized
coordination, and state management for elastic processes. Furthermore, we
present two representative elastic Business Process Management Systems which
are intended to counter these challenges. Based on our findings, we identify
open issues and outline possible research directions for the realization of
elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and
P. Hoenisch (2015). Elastic Business Process Management: State of the Art and
Open Challenges for BPM in the Cloud. Future Generation Computer Systems,
Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00
Software-Driven and Virtualized Architectures for Scalable 5G Networks
In this dissertation, we argue that it is essential to rearchitect 4G cellular core networks–sitting between the Internet and the radio access network–to meet the scalability, performance, and flexibility requirements of 5G networks. Today, there is a growing consensus among operators and research community that software-defined networking (SDN), network function virtualization (NFV), and mobile edge computing (MEC) paradigms will be the key ingredients of the next-generation cellular networks. Motivated by these trends, we design and optimize three core network architectures, SoftMoW, SoftBox, and SkyCore, for different network scales, objectives, and conditions. SoftMoW provides global control over nationwide core networks with the ultimate goal of enabling new routing and mobility optimizations. SoftBox attempts to enhance policy enforcement in statewide core networks to enable low-latency, signaling-efficient, and customized services for mobile devices. Sky- Core is aimed at realizing a compact core network for citywide UAV-based radio networks that are going to serve first responders in the future. Network slicing techniques make it possible to deploy these solutions on the same infrastructure in parallel. To better support mobility and provide verifiable security, these architectures can use an addressing scheme that separates network locations and identities with self-certifying, flat and non-aggregatable address components. To benefit the proposed architectures, we designed a high-speed and memory-efficient router, called Caesar, for this type of addressing schemePHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146130/1/moradi_1.pd
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