826404
On the effectiveness of secure overlay forwarding systems under intelligent distributed DoS attacks
In the framework of a set of clients communicating with a critical server over the Internet, a recent approach to protect communication from distributed denial of service (DDoS) attacks involves the usage of overlay systems. SOS, MAYDAY, and I3 are such systems. The architecture of these systems consists of a set of overlay nodes that serve as intermediate forwarders between the clients and the server, thereby controlling access to the server. Although such systems perform well under random DDoS attacks, it is questionable whether they are resilient to intelligent DDoS attacks which aim to infer architectures of the systems to launch more efficient attacks. In this paper, we define several intelligent DDoS attack models and develop analytical/simulation approaches to study the impacts of architectural design features of such, overlay systems on the system performance in terms of path availability between clients and the server under attacks. Our data clearly demonstrate that the system performance is indeed sensitive to the architectural features and the different features interact with each other to impact overall system performance under intelligent DDoS attacks. Our observations provide important guidelines in the design of such secure overlay forwarding systems
36451114
Sensor Network Configuration Under Physical Attacks
Sensor networks typically operate in hostile outdoor environments. In such environments, sensor networks are highly susceptible to physical attacks that can result in physical node destructions. In this paper, we study the impacts of physical attacks on sensor network configuration. Lifetime is an important metric during configuration for many sensor applications. While lifetime is constrained by limited energies and has been addressed before, prior results cannot be directly applied in the presence of physical attacks. In this paper, we define a practical lifetime problem in sensor networks under a representative physical attack model that we define. We develop an anlytical approach to derive the minimum number and deployment plan of sensors to meet lifetime requirement under physical attacks. We make several observations in this paper. One of our important observations is the high sensitivity of lifetime to physical attacks highlighting the significance of our study.
631362
DEUCON: Decentralized End-to-End Utilization Control for Distributed Real-Time Systems
Many real-time systems must control their CPU utilizations in order to meet end-to-end deadlines and prevent overload. Utilization control is particularly challenging in distributed real-time systems with highly unpredictable workloads and a large number of end-to-end tasks and processors. This paper presents the decentralized end-to-end utilization control (DEUCON) algorithm, which can dynamically enforce the desired utilizations on multiple processors in such systems. In contrast to centralized control schemes adopted in earlier works, DEUCON features a novel decentralized control structure that requires only localized coordination among neighbor processors. DEUCON is systematically designed based on advances in distributed model predictive control theory. Both control-theoretic analysis and simulations show that DEUCON can provide robust utilization guarantees and maintain global system stability despite severe variations in task execution times. Furthermore, DEUCON can effectively distribute the computation and communication cost to different processors and tolerate considerable communication delay between local controllers. Our results indicate that DEUCON can provide a scalable and robust utilization control for large-scale distributed real-time systems executing in unpredictable environments.
14150285
A pipeline for rapidly incorporating real objects into a mixed environment
A method is presented to rapidly incorporate real objects into virtual environments using laser scanned 3D models with color-based marker tracking. Both the real objects and their geometric models are put into a mixed environment (ME). In the ME, users can manipulate the scanned, articulated real objects, such as tools, parts, and physical correlates to complex computer-aided design (CAD) models. Our aim is to allow engineering teams to effectively conduct hands-on assembly design verification. This task would be simulated at a high degree of fidelity, and would benefit from the natural interaction afforded by a ME with many specific real objects.
5719252
End-to-end utilization control in distributed real-time systems
An increasing number of distributed real-time systems face the critical challenge of providing end-to-end quality of service (QoS) guarantees in open and unpredictable environments. In particular, such systems often need to guarantee the CPU utilization on multiple processors in order to achieve overload protection and meet end-to-end deadlines while task execution times are unpredictable. While the recently developed feedback control real-time scheduling algorithms have shown promise, they cannot handle the common end-to-end task model in distributed systems where each task is comprised of a chain of subtasks distributed on multiple processors. We present the end-to-end utilization control (EUCON) algorithm that features a distributed feedback loop that dynamically enforces desired CPU utilization bounds on multiple processors based on online performance measurements EUCON is based on a model predictive control approach that models the utilization control problem on a distributed platform as a multivariable constrained optimization problem. A multiinput-multioutput model predictive controller is designed based on a difference equation model that describes the dynamic behavior of distributed real-time systems. Both control theoretic analysis and simulations demonstrate that EUCON can provide robust utilization guarantees even when task execution times deviate from the estimation or vary significantly at run-time.
7656393
CAMRIT: control-based adaptive middleware for real-time image transmission
Real-time image transmission is crucial to an emerging class of distributed embedded systems operating in open network environments. Examples include avionics mission re-planning over Link-16, security systems based on wireless camera networks, and online collaboration using camera phones. Meeting image transmission deadlines is a key challenge in such systems due to unpredictable network conditions. In this paper, we present CAMRIT, a control-based adaptive middleware framework for real-time image transmission in distributed real-time embedded systems. CAMRIT features a distributed feedback control loop that meets image transmission deadlines by dynamically adjusting the quality of image tiles. We derive an analytic model that captures the dynamics of a distributed middleware architecture. A control theoretic methodology is applied to systematically design a control algorithm with analytic assurance of system stability and performance, despite uncertainties in network bandwidth. Experimental results demonstrate that CAMRIT can provide robust real-time guarantees for a representative application scenario.
53307075
Effects of Neuromodulation in a Cortical Network Model of Object Working Memory Dominated by Recurrent Inhibition
Experimental evidence suggests that the maintenance of an item in working memory is achieved through persistent activity in selective neural assemblies of the cortex. To understand the mechanisms underlying this phenomenon, it is essential to investigate how persistent activity is affected by external inputs or neuromodulation. We have addressed these questions using a recurrent network model of object working memory. Recurrence is dominated by inhibition, although persistent activity is generated through recurrent excitation in small subsets of excitatory neurons.Our main findings are as follows. (1) Because of the strong feedback inhibition, persistent activity shows an inverted U shape as a function of increased external drive to the network. (2) A transient external excitation can switch off a network from a selective persistent state to its spontaneous state. (3) The maintenance of the sample stimulus in working memory is not affected by intervening stimuli (distractors) during the delay period, provided the stimulation intensity is not large. On the other hand, if stimulation intensity is large enough, distractors disrupt sample-related persistent activity, and the network is able to maintain a memory only of the last shown stimulus. (4) A concerted modulation of GABAA and NMDA conductances leads to a decrease of spontaneous activity but an increase of persistent activity; the enhanced signal-to-noise ratio is shown to increase the resistance of the network to distractors. (5) Two mechanisms are identified that produce an inverted U shaped dependence of persistent activity on modulation. The present study therefore points to several mechanisms that enhance the signal-to-noise ratio in working memory states. These mechanisms could be implemented in the prefrontal cortex by dopaminergic projections from the midbrain.