77,627 research outputs found
Addressing the Challenges in Federating Edge Resources
This book chapter considers how Edge deployments can be brought to bear in a
global context by federating them across multiple geographic regions to create
a global Edge-based fabric that decentralizes data center computation. This is
currently impractical, not only because of technical challenges, but is also
shrouded by social, legal and geopolitical issues. In this chapter, we discuss
two key challenges - networking and management in federating Edge deployments.
Additionally, we consider resource and modeling challenges that will need to be
addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and
Paradigms; Editors Buyya, Sriram
ENORM: A Framework For Edge NOde Resource Management
Current computing techniques using the cloud as a centralised server will
become untenable as billions of devices get connected to the Internet. This
raises the need for fog computing, which leverages computing at the edge of the
network on nodes, such as routers, base stations and switches, along with the
cloud. However, to realise fog computing the challenge of managing edge nodes
will need to be addressed. This paper is motivated to address the resource
management challenge. We develop the first framework to manage edge nodes,
namely the Edge NOde Resource Management (ENORM) framework. Mechanisms for
provisioning and auto-scaling edge node resources are proposed. The feasibility
of the framework is demonstrated on a PokeMon Go-like online game use-case. The
benefits of using ENORM are observed by reduced application latency between 20%
- 80% and reduced data transfer and communication frequency between the edge
node and the cloud by up to 95\%. These results highlight the potential of fog
computing for improving the quality of service and experience.Comment: 14 pages; accepted to IEEE Transactions on Services Computing on 12
September 201
Information dynamics shape the networks of Internet-mediated prostitution
Like many other social phenomena, prostitution is increasingly coordinated
over the Internet. The online behavior affects the offline activity; the
reverse is also true. We investigated the reported sexual contacts between
6,624 anonymous escorts and 10,106 sex-buyers extracted from an online
community from its beginning and six years on. These sexual encounters were
also graded and categorized (in terms of the type of sexual activities
performed) by the buyers. From the temporal, bipartite network of posts, we
found a full feedback loop in which high grades on previous posts affect the
future commercial success of the sex-worker, and vice versa. We also found a
peculiar growth pattern in which the turnover of community members and sex
workers causes a sublinear preferential attachment. There is, moreover, a
strong geographic influence on network structure-the network is geographically
clustered but still close to connected, the contacts consistent with the
inverse-square law observed in trading patterns. We also found that the number
of sellers scales sublinearly with city size, so this type of prostitution does
not, comparatively speaking, benefit much from an increasing concentration of
people
Designing Scalable Business Models
Digital business models are often designed for rapid growth, and some relatively young companies have indeed achieved global scale. However despite the visibility and importance of this phenomenon, analysis of scale and scalability remains underdeveloped in management literature. When it is addressed, analysis of this phenomenon is often over-influenced by arguments about economies of scale in production and distribution. To redress this omission, this paper draws on economic, organization and technology management literature to provide a detailed examination of the sources of scaling in digital businesses. We propose three mechanisms by which digital business models attempt to gain scale: engaging both non- paying users and paying customers; organizing customer engagement to allow self- customization; and orchestrating networked value chains, such as platforms or multi-sided business models. Scaling conditions are discussed, and propositions developed and illustrated with examples of big data entrepreneurial firms
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