653436
Integrated coverage and connectivity configuration for energy conservation in sensor networks
An effective approach for energy conservation in wireless sensor networks is scheduling sleep intervals for extraneous nodes while the remaining nodes stay active to provide continuous service. For the sensor network to operate successfully, the active nodes must maintain both sensing coverage and network connectivity. Furthermore, the network must be able to configure itself to any feasible degree of coverage and connectivity in order to support different applications and environments with diverse requirements. This article presents the design and analysis of novel protocols that can dynamically configure a network to achieve guaranteed degrees of coverage and connectivity. This work differs from existing connectivity or coverage maintenance protocols in several key ways. (1) We present a Coverage Configuration Protocol (CCP) that can provide different degrees of coverage requested by applications. This flexibility allows the network to self-configure for a wide range of applications and (possibly dynamic) environments. (2) We provide a geometric analysis of the relationship between coverage and connectivity. This analysis yields key insights for treating coverage and connectivity within a unified framework; in sharp contrast to several existing approaches that address the two problems in isolation. (3) We integrate CCP with SPAN to provide both coverage and connectivity guarantees. (4) We propose a probabilistic coverage model and extend CCP to provide probabilistic coverage guarantees. We demonstrate the capability of our protocols to provide guaranteed coverage and connectivity configurations through both geometric analysis and extensive simulations.
269391
Integrated coverage and connectivity configuration in wireless sensor networks
An effective approach for energy conservation in wireless sensor networks is scheduling sleep intervals for extraneous nodes, while the remaining nodes stay active to provide continuous service. For the sensor network to operate successfully, the active nodes must maintain both sensing coverage and network connectivity. Furthermore, the network must be able to configure itself to any feasible degrees of coverage and connectivity in order to support different applications and environments with diverse requirements. This paper presents the design and analysis of novel protocols that can dynamically configure a network to achieve guaranteed degrees of coverage and connectivity. This work differs from existing connectivity or coverage maintenance protocols in several key ways: 1) We present a Coverage Configuration Protocol (CCP) that can provide different degrees of coverage requested by applications. This flexibility allows the network to self-configure for a wide range of applications and (possibly dynamic) environments. 2) We provide a geometric analysis of the relationship between coverage and connectivity. This analysis yields key insights for treating coverage and connectivity in a unified framework: this is in sharp contrast to several existing approaches that address the two problems in isolation. 3) Finally, we integrate CCP with SPAN to provide both coverage and connectivity guarantees. We demonstrate the capability of our protocols to provide guaranteed coverage and connectivity configurations, through both geometric analysis and extensive simulations.
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.
15273314
Feedback control real-time scheduling in ORB middleware
Existing real-time ORB middleware standards such as RT-CORBA do not adequately address the challenges of 1) providing robust performance guarantees portably across different platforms, and 2) managing unpredictable workload. To overcome this limitation, we have developed software called FCS/nORB that integrates a Feedback Control real-lime Scheduling (FCS) service with the nORB small-footprint real-time ORB designed for networked embedded systems. FCS/nORB features feedback control loops that provide real-time performance guarantees by automatically adjusting the rate of remote method invocations transparently to an application. FCS/nORB thus enables real-time applications to be truly portable in terms of real-time performance as well as functionality, without the need for hand tuning. This paper presents the design, implementation, and evaluation of FCS/nORB. Our extensive experiments on a Linux testbed demonstrate that FCS can provide deadline miss ratio and utilization guarantees in face of changes in the platform and task execution times, while introducing a small amount of overhead.
5867346
Feedback utilization control in distributed real-time systems with end-to-end tasks
An increasing number of distributed real-time systems face the critical challenge of providing quality of service guarantees in open and unpredictable environments. In particular, such systems often need to enforce utilization bounds on multiple processors in order to avoid overload and meet end-to-end deadlines even when task execution times are unpredictable. While recent feedback control real-time scheduling algorithms have shown promise, they cannot handle the common end-to-end task model where each task is comprised of a chain of subtasks distributed on multiple processors. This paper presents the end-to-end utilization control (EUCON) algorithm that adaptively maintains desired CPU utilization through performance feedbacks loops. EUCON is based on a model predictive control approach that models utilization control on a distributed platform as a multivariable constrained optimization problem. A multi-input-multi-output 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 when task execution times deviate from estimation or vary significantly at runtime.
1347401
Decentralized utilization control in 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 that can dynamically enforce desired utilizations on multiple processors in such systems. In contrast to centralized control schemes adopted in earlier work, DEUCON features a novel decentralized control structure that only requires localized coordination among neighbor processors. DEUCON is systematically designed based on recent 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 scalable and robust utilization control for large-scale distributed real-time systems executing in unpredictable environments
6847194
Analyzing the secure overlay services architecture under intelligent DDoS attacks
Distributed denial of service (DDoS) attacks are currently major threats to communication in the Internet. A secure overlay services (SOS) architecture has been proposed to provide reliable communication between clients and a target under DDoS attacks. The SOS architecture employs a set of overlay nodes arranged in three hierarchical layers that controls access to the target. Although the architecture is novel and works well under simple congestion based attacks, we observe that it is vulnerable under more intelligent attacks. We generalize the SOS architecture by introducing more flexibility in layering to the original architecture. We define two intelligent DDoS attack models and develop an analytical approach to study the impacts of the number of layers, number of neighbors per node and the node distribution per layer on the system performance under these two attack models. Our data clearly demonstrate that performance is indeed sensitive to the design features and the different design features interact with each other to impact overall system performance.
36117076
Discovering Frequent Event Patterns with Multiple Granularities in Time Sequences
An important usage of time sequences is to discover temporal patterns. The discovery process usually starts with a user specified skeleton, called an event structure, which consists of a number of variables representing events and temporal constraints among these variables; the goal of the discovery is to find temporal patterns, i.e., instantiations of the variables in the structure that appear frequently in the time sequence. The paper introduces event structures that have temporal constraints with multiple granularities, defines the pattern discovery problem with these structures, and studies effective algorithms to solve it. The basic components of the algorithms include timed automata with granularities (TAGs) and a number of heuristics. The TAGs are for testing whether a specific temporal pattern, called a candidate complex event type, appears frequently in a time sequence. Since there are often a huge number of candidate event types for a usual event structure, heuristics are presented aiming at reducing the number of candidate event types and reducing the time spent by the TAGs testing whether a candidate type does appear frequently in the sequence. These heuristics exploit the information provided by explicit and implicit temporal constraints with granularity in the given event structure. The paper also gives the results of an experiment to show the effectiveness of the heuristics on a real data set.
149826
Generalized component analysis for text with heterogeneous attributes
We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. Our model generalizes techniques such as principal component analysis to heterogeneous data types. In contrast to other approaches, this framework allows modalities such as words, authors and timestamps to be captured in their natural, probabilistic encodings. A latent space representation for a previously unseen document can be obtained through a fast matrix multiplication using our method. We demonstrate the effectiveness of our framework on the task of author prediction from 13 years of the NIPS conference proceedings and for a recipient prediction task using a 10-month academic email archive of a researcher. Our approach should be more broadly applicable to many real-world applications where one wishes to efficiently make predictions for a large number of potential outputs using dimensionality reduction in a well defined probabilistic framework.
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.
3413304
On Node Isolation Under Churn in Unstructured P2P Networks with Heavy-Tailed Lifetimes
Previous analytical studies [12], [18] of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared to uniform selection of neighbors. In fact, the second strategy based on random walks on age-weighted graphs demonstrates that for lifetimes with infinite variance, the system monotonically increases its resilience as its age and size grow. Specifically, we show that the probability of isolation converges to zero as these two metrics tend to infinity. We finish the paper with simulations in finite-size graphs that demonstrate the effect of this result in practice.