Engineering topics

Lagesse, Brent J

Publications and source records attributed to Lagesse, Brent J.

4 records

DOE OSTI2011

Challenges in Securing the Interface Between the Cloud and Pervasive Systems

Cloud computing presents an opportunity for pervasive systems to leverage computational and storage resources to accomplish tasks that would not normally be possible on such resource-constrained devices. Cloud computing can enable hardware designers to build lighter systems that last longer and are more mobile. Despite the advantages cloud computing offers to the designers of pervasive systems, there are some limitations of leveraging cloud computing that must be addressed. We take the position that cloud-based pervasive system must be secured holistically and discuss ways this might be accomplished. In this paper, we discuss a pervasive system utilizing cloud computing resources and issues that must be addressed in such a system. In this system, the user's mobile device cannot always have network access to leverage resources from the cloud, so it must make intelligent decisions about what data should be stored locally and what processes should be run locally. As a result of these decisions, the user becomes vulnerable to attacks while interfacing with the pervasive system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2011

Embracing the Cloud for Better Cyber Security

The future of cyber security is inextricably tied to the future of computing. Organizational needs and economic factors will drive computing outcomes. Cyber security researchers and practitioners must recognize the path of computing evolution and position themselves to influence the process to incorporate security as an inherent property. The best way to predict future computing trends is to look at recent developments and their motivations. Organizations are moving towards outsourcing their data storage, computation, and even user desktop environments. This trend toward cloud computing has a direct impact on cyber security: rather than securing user machines, preventing malware access, and managing removable media, a cloud-based security scheme must focus on enabling secure communication with remote systems. This change in approach will have profound implications for cyber security research efforts. In this work, we highlight existing and emerging technologies and the limitations of cloud computing systems. We then discuss the cyber security efforts that would support these applications. Finally, we discuss the implications of these computing architecture changes, in particular with respect to malware and social engineering.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2011

Challenges in Scheduling Aggregation in CyberPhysical Information Processing Systems

Data aggregation (a.k.a reduce operations) is an important element in information processing systems, including MapReduce clusters and cyberphysical networks. Unlike simple sensor networks, all the data in information processing systems must be eventually aggregated. Our goal is to lower overall latency in these systems by intelligently scheduling aggregation on intermediate routing nodes. Unlike previous models, our model explicitly takes into account link latency and computa- tion time. Our model also considers heterogeneous computing capabilities. In order to understand the potential challenges associated with constructing a distributed scheduler that minimizes la- tency, we ve developed a simulation of our model and tested the results of randomly scheduling nodes. Although these experiments were designed to provide data for a null-model, preliminary results have yielded a few interesting observations. We show that in cases where the computation time is larger than transmission time, in-network aggregation can have a large effect (reducing latency by 50% or more), but that naive scheduling can have a detrimental effect. Specifically, we show that when the root node (a.k.a the basestation) is faster than the other nodes, the latency can increase with increased coverage, and that these effects vary with the number of nodes present.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2011

Latency Minimizing Tasking for Information Processing Systems

Real-time cyber-physical systems and information processing clusters require system designers to consider the total latency involved in collecting and aggregating data. For example, applications such as wild-fire monitoring require data to be presented to users in a timely manner. However, most models and algorithms for sensor networks have focused on alternative metrics such as energy efficiency. In this paper, we present a new model of sensor network aggregation that focuses on total latency. Our model is flexible and enables users to configure varying transmission and computation time on a node-by-node basis, and thus enables the simulation of complex computational phenomena. In addition, we present results from three tasking algorithms that trade-off local communication for overall latency performance. These algorithms are evaluated in simulated networks of up to 200 nodes. We've presented an aggregation-focused model of sensor networks that can be used to study the trade-offs between computational coverage and total latency. Our model explicitly takes into account transmission and computation times, and enables users to define different values for the basestation. In addition, we've presented three different tasking algorithms that operate over model to produce aggregation schedules of varying quality. In the future, we expect to continue exploring distributed tasking algorithms for information processing systems. We've shown that the gap between highly optimized schedules that use global information is quite large relative to our distributed algorithms. This gives us encouragement that future distributed tasking algorithms can still make large gains.

99 GENERAL AND MISCELLANEOUS↗