Trustee: A Trust Management System for Fog-enabled Cyber Physical Systems

In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, badmouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasures the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e. CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system

MorphoSys: efficient colocation of QoS-constrained workloads in the cloud

In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the host’s resources. In this paper, we propose that periodic resource allocation and consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS.National Science Foundation (0720604, 0735974, 0820138, 0952145, 1012798

Correlated multi-streaming in distributed interactive multimedia systems

Distributed Interactive Multimedia Environments (DIMEs) enable geographically distributed people to interact with each other in a joint media-rich virtual environment for a wide range of activities, such as art performance, medical consultation, sport training, etc. The real-time collaboration is made possible by exchanging a set of multi-modal sensory streams over the network in real time. The characterization and evaluation of such multi-stream interactive environments is challenging because the traditional Quality of Service metrics (e.g., delay, jitter) are limited to a per stream basis. In this work, we present a novel ???Bundle of Streams??? concept to de???ne correlated multi-streams in DIMEs and present new cyber-physical, spatio-temporal QoS metrics to measure QoS over bundle of streams. We realize Bundle of Streams concept by presenting a novel paradigm of Bundle Streaming as a Service (SAS). We propose and develop SAS Kernel, a generic, distributed, modular and highly ???exible streaming kernel realizing SAS concept. We validate the Bundle of Streams model by comparing the QoS performance of bundle of streams over different transport protocols in a 3D tele-immersive testbed. Also, further experiments demonstrate that the SAS Kernel incurs low overhead in delay, CPU, and bandwidth demands