This paper discusses the challenges in computer systems research posed by the emerging field of pervasive computing. It first examines the relationship of this new field to its predecessors: distributed systems and mobile computing. It then identifies four new research thrusts: effective use

Abstract Efficient key distribution is the basis for providing secure communication, a necessary requirement for many emerging sensor network applications. Many applications require authentic and secret communication among neighboring sensor nodes. However, establishing keys for secure

fic web site and enter their current location and destination. Although this is a powerful capability, it nonetheless requires the user to remember to check in a timely manner to adjust their route or leave earlier than forecast and to enter mundane data into the user interface. In ubiquitous computing, an autonomous agent would constantly be checking the user's current location (available from GPS or in-building wireless infrastructure) and their calendar to determine if an adjustment in schedule should be made. If traffic conditions warrant it, the user can be signaled and their PDA can show a brief reminder with the minutes left before they should head off. Another example uses a biologist in a laboratory that would like to record all the steps in their experimental protocol so that others can faithfully reproduce them. Traditional computing would provide the biologist with a PDA or laptop in which to enter each step but requiring the biologist to interrupt the flow of their work to

the key elements of the emergent technology of “Smart Dust ” and outline the research challenges they present to the mobile networking and systems community, which must provide coherent connectivity to large numbers of mobile network nodes co-located within a small volume.

expectations of end-to-end connectivity and node resources. The architecture operates as an overlay above the transport layers of the networks it interconnects, and provides key services such as in-network data storage and retransmission, interoperable naming, authenticated forwarding and a coarse

Reliability at massive scale is one of the biggest challenges we face at Amazon.com, one of the largest e-commerce operations in the world; even the slightest outage has significant financial consequences and impacts customer trust. The Amazon.com platform, which provides services for many web

Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses

to be used in a nearest-neighbor framework. Making use of noisy optical flow measurements is the key challenge, which is addressed by treating optical flow not as precise pixel displacements, but rather as a spatial pattern of noisy measurements which are carefully smoothed and aggregated to form our spatio

and globalization is to provide individuals the ability to transform information into socially beneficial knowledge, skills, and value; modernize societies and improve the standard of living (Masood, 2010, Kong and Li, 2009 and Ng et al., 2006). This paper examined some key challenges faced by the higher education

In this survey, we review work in machine learning on methods for handling data sets containing large amounts of irrelevant information. We focus on two key issues: the problem of selecting relevant features, and the problem of selecting relevant examples. We describe the advances that have been