Local Information Exchange Research Articles

Plantwide process control with asynchronous sampling and communications

Abstract The need for economic efficiency has driven the development of large and complex chemical plants. These plants typically contain a large number of process units, often with different time scales, interacting with each other due to the use of recycle streams and heat integration. This causes considerable difficulties in plantwide control. This paper aims to address this issue by developing a flexible networked-based plantwide control approach. In this approach, a plantwide process is modeled as a network of process units which is controlled by a network of autonomous controllers. The controllers within the network operate with different sampling rates and communicate with each other asynchronously, to allow cost-effective control designs and efficient utilization of communication bandwidth. This networked control approach ensures the plantwide stability even when communications between controllers breakdown. Using the concept of dissipative systems, the effects of different local controller sampling rates and information exchange rates on the stability and performance of the entire plant are represented by a set of dissipativity conditions. The conditions that individual local controller has to satisfy to achieve the plantwide stability and user specified performance are derived. Autonomous controllers can then be designed individually to form a controller network. This effectiveness of the proposed approach is demonstrated by an illustrative example of a process network that consists of a reactor and a multi-stages distillation column.

Configuring Trees of Classifiers in Distributed Multimedia Stream Mining Systems

Multimedia stream mining applications require the identification of several different attributes in data content, and hence rely on a set of cascaded statistical classifiers to filter and process the data dynamically. In this paper, we introduce a novel methodology for configuring such cascaded classifier topologies, specifically binary classifier trees, in resource-constrained, distributed stream mining systems. Instead of traditional load shedding, our approach configures classifiers with optimized operating points after jointly considering the misclassification cost of each end-to-end class of interest in the tree, the resource constraints for every classifier, and the confidence level of each data object that is classified. The proposed approach allows for both intelligent load shedding as well as data replication based on available resources dynamically. We evaluate the algorithm on a sports video concept detection application and identify huge cost savings over load shedding alone. Additionally, we propose several distributed algorithms that enable each classifier in the tree to reconfigure itself based on local information exchange. We analyze the associated tradeoffs between convergence time, information overhead, and the cost efficiency of results achieved by each classifier for each of these algorithms.

Scalable Network Synchronization with Pulse-Coupled Oscillators

The Pulse-Coupled Oscillator (PCO) is a novel protocol inspired by models used in mathematical biology to justify the emergence of synchrony in the natural world. Our paper introduces and demonstrates the efficacy of a new PCO protocol implementation that, by disabling all collision resolution mechanisms for a suitable portion of the node operations, lets the rapid establishment of a common clock and its maintenance. The key idea is to allow signals to be superimposed in time, a feature that is absent in previous implementations, because it is prevented by traditional medium access schemes. We map the PCO protocol into an event-driven asynchronous coloring algorithm, based on the local exchange of information to explain its convergence properties. The event-based description of the PCO protocol sets the stage for our experimental comparison with a competing decentralized network synchronization approach, namely, the Reference Broadcast Protocol (RBS). For comparison, we combined RBS with an asynchronous average consensus protocol, running exactly on the same MicaZ platforms. The experimental results showcase the better scalability of the PCO scheme compared to the competing method based on RBS, proving that the PCO primitive is a reasonable option to consider for wireless sensor network applications.

Consensus-Based Cooperative Spectrum Sensing with Improved Robustness Against SSDF Attacks

Based on the consensus algorithm, an attack-proof cooperative spectrum sensing (CSS) scheme is presented for decentralized cognitive radio networks (CRNs), where a common fusion center is not available and some malicious users may launch attacks with spectrum sensing data falsification (SSDF). Local energy detection is firstly performed by each secondary user (SU), and then, utilizing the consensus notions, each SU can make its own decision individually only by local information exchange with its neighbors rather than any centralized fusion used in most existing schemes. With the help of some anti-attack tricks, each authentic SU can generally identify and exclude those malicious reports during the interactions within the neighborhood. Compared with the existing solutions, the proposed scheme is proved to have much better robustness against three categories of SSDF attack, without requiring any a priori knowledge of the whole network.

On consensus algorithms for double-integrator dynamics without velocity measurements and with input constraints

This note deals with consensus strategy design for double-integrator dynamics. Specifically, we consider the case where the control inputs are required to be a priori bounded and the velocity (second state) is not available for feedback. Two different design methods are proposed. First, based on the auxiliary system approach, we propose a consensus algorithm that extends some of the existing results in the literature to account for actuator saturations and the lack of velocity measurement. The proposed velocity-free control scheme, using local information exchange, achieves consensus among the team members with an a priori bounded control law, whose upper bound depends on the number of neighbors of the vehicle. Second, we propose another approach based on the use of a high order dynamic auxiliary system such that the upper bound of the control law is independent of the number of neighbors of the vehicle, and the performance of the closed loop system is improved in terms of the response damping. Finally, simulation results are provided to illustrate the effectiveness of the proposed algorithms.

Distributed user profiling via spectral methods

User profiling is a useful primitive for constructing personalized services, such as content recommendation. In the present work we investigate the feasibility of user profiling in a distributed setting, with no central authority and only local information exchanges between users. Our main contributions are: (i)~We propose a spectral clustering technique, and prove its ability to recover unknown user profiles with only few measures of affinity between users. (ii)~We develop distributed algorithms which achieve an embedding of users into a low-dimensional space, based on spectral transformation. These involve simple message passing among users, and provably converge to the desired embedding.

Multiscale decision-making: Bridging organizational scales in systems with distributed decision-makers

Decision-making in organizations is complex due to interdependencies among decision-makers (agents) within and across organizational hierarchies. We propose a multiscale decision-making model that captures and analyzes multiscale agent interactions in large, distributed decision-making systems. In general, multiscale systems exhibit phenomena that are coupled through various temporal, spatial and organizational scales. Our model focuses on the organizational scale and provides analytic, closed-form solutions which enable agents across all organizational scales to select a best course of action. By setting an optimal intensity level for agent interactions, an organizational designer can align the choices of self-interested agents with the overall goals of the organization. Moreover, our results demonstrate when local and aggregate information exchange is sufficient for system-wide optimal decision-making. We motivate the model and illustrate its capabilities using a manufacturing enterprise example.

Internet Use and the Concentration of Disadvantage: Glocalization and the Urban Underclass

This article argues that the literature on digital inequality—in its focus on individual characteristics, behaviors, and outcomes—has overlooked change within the context of where social and civic inequalities are reproduced. This omission is the result of a failure to explore the role of ecological context within the study of the digital divide and the role of communication within the study of collective efficacy. Social cohesion, and an expectation for informal social control at the neighborhood level, is a function of both ecological context and media context. Those embedded within settings where prior media, including the telephone and face-to-face contact, could not overcome contextual barriers to collective action, namely within areas of concentrated disadvantage; may now, as a result of local Internet use, experience reduced social and civic inequality. This article is based on the results of a 3-year naturalistic experiment that examined the use of the Internet for communication at the neighborhood level. It proposes a new measure of collective efficacy — in place of network measures or perceived cohesion — based on the direct observation of communication practices. The analysis includes a model of the ecological characteristics associated with neighborhoods that adopted the Internet as a means of local information exchange, and it provides a comparison of the content of electronic messages exchanged within areas of advantage and those of extreme poverty, unemployment, and racial segregation. Findings suggest that as much as the Internet supports social and civic engagement in areas where it is already likely to be high, it also affords engagement within contexts of extreme disadvantage.

Performance metrics in the consensus problem: a Survey

Linear consensus is a distributed algorithm which ensures that, under certain assumptions, a set of agents reach asymptotically the same opinion over a certain variable. Moreover this occurs with only a local exchange of information, namely the information exchange takes place only between agents which are neighbors in a graph representing the system communication architecture. Several performance metrics have been proposed for the evaluation of this algorithm. Particularly interesting and challenging is to relate performance to the communication topology. Different performance metrics may yield to different answers in comparing alternative communication topologies. In this paper, we present a number of possible performance metrics. Moreover, we show how these metrics are related to the communication topology. In particular, when available, we present bounds by which it is possible to relate performance and topology for general graphs, for graphs with symmetries, called Cayley graphs, and for geometric graphs.

A Distributed Consensus-Based Cooperative Spectrum-Sensing Scheme in Cognitive Radios

In cognitive radio (CR) networks, secondary users can cooperatively sense the spectrum to detect the presence of primary users. In this paper, we propose a fully distributed and scalable cooperative spectrum-sensing scheme based on recent advances in consensus algorithms. In the proposed scheme, the secondary users can maintain coordination based on only local information exchange without a centralized common receiver. Unlike most of the existing decision rules, such as the or-rule or the 1-out-of-N rule, we use the consensus of secondary users to make the final decision. Simulation results show that the proposed consensus scheme can have significant lower missing detection probabilities and false alarm probabilities in CR networks. It is also demonstrated that the proposed scheme not only has proven sensitivity in detecting the primary user's presence but also has robustness in choosing a desirable decision threshold.

Distributed and localized construction of routing structure for sensor data gathering

Several routing structures have been proposed for data gathering in a wireless sensor network. They are considered to be near-optimal with respect to energy efficiency or delivery delay, but they overlook the construction cost of a routing tree which may make trouble in implementation. Our primary goal in this work is to construct a routing tree with negligible cost, which performs as well as those near-optimal schemes. First, we propose a distributed and localized framework for tree construction called Local Parent Designation (LPD), where the node status information is exchanged locally and decision based on the local information leads us to construct a routing tree. Secondly, we extend LPD to so called LPD-Local Fix (LPD-LF) to reduce further the construction cost with less local information exchange. Simulation results validate that our goal is achieved.

The formation and evolution of physician treatment styles: An application to cesarean sections

Small-area-variation studies have shown that physician treatment styles differ substantially both between and within markets, controlling for patient characteristics. Using data on the universe of deliveries in Florida and New York over a 15-year period, we examine why treatment styles differ across obstetricians at a point in time and why styles change over time. We find that variation in c-section rates across physicians within a market is about twice as large as variation between markets. Surprisingly, residency programs explain no more than four percent of the variation in physicians' risk-adjusted c-section rates, even among newly trained physicians. Although we find evidence that physicians learn from their peers, they do not substantially revise their prior beliefs regarding treatment due to the local exchange of information. Our results indicate that physicians are not likely to converge over time to a community standard; thus, within-market variation in treatment styles is likely to persist.

Constraint satisfaction problems and neural networks: A statistical physics perspective

A new field of research is rapidly expanding at the crossroad between statistical physics, information theory and combinatorial optimization. In particular, the use of cutting edge statistical physics concepts and methods allow one to solve very large constraint satisfaction problems like random satisfiability, coloring, or error correction. Several aspects of these developments should be relevant for the understanding of functional complexity in neural networks. On the one hand the message passing procedures which are used in these new algorithms are based on local exchange of information, and succeed in solving some of the hardest computational problems. On the other hand some crucial inference problems in neurobiology, like those generated in multi-electrode recordings, naturally translate into hard constraint satisfaction problems. This paper gives a non-technical introduction to this field, emphasizing the main ideas at work in message passing strategies and their possible relevance to neural networks modelling. It also introduces a new message passing algorithm for inferring interactions between variables from correlation data, which could be useful in the analysis of multi-electrode recording data.

On the performance of distributed lightpath provisioning with dynamic routing and wavelength assignment

Distributed lightpath provisioning in wavelength-division multiplexing (WDM) networks has gained wide research interests. In this article, we study the performance of distributed lightpath provisioning in WDM networks with dynamic routing and wavelength assignment (RWA). Specifically, we consider the case where routing of each lightpath is calculated based on globally flooded link-state information, and wavelength assignment is decided through local information exchanges. Simulation results show that such schemes steadily outperform those schemes with only global flooding or only local information exchanges. More significantly, the impacts of various factors on the proposed scheme, including RWA algorithm, network topology, number of wavelengths per fiber, global flooding interval, and traffic load, have been evaluated. Such evaluations help to achieve some insights useful for the future developments of efficient lightpath provisioning schemes.

Distributed Scheduling and Resource Allocation for Cognitive OFDMA Radios

Scheduling spectrum access and allocating power and rate resources are tasks affecting critically the performance of wireless cognitive radio (CR) networks. The present contribution develops a primal-dual optimization framework to schedule any-to-any CR communications based on orthogonal frequency division multiple access and allocate power so as to maximize the weighted average sum-rate of all users. Fairness is ensured among CR communicators and possible hierarchies are respected by guaranteeing minimum rate requirements for primary users while allowing secondary users to access the spectrum opportunistically. The framework leads to an iterative channel-adaptive distributed algorithm whereby nodes rely only on local information exchanges with their neighbors to attain global optimality. Simulations confirm that the distributed online algorithm does not require knowledge of the underlying fading channel distribution and converges to the optimum almost surely from any initialization.

A TTP-free protocol for location privacy in location-based services

Location-based services (LBS) will be a keystone of the new information society that is founded on the information and communications technologies (ICTs). Mobile devices such as cell phones or laptops have become ubiquitous. They are equipped with a variety of localisation systems that make them proper for making use of the new LBS. Most of the times, these services are provided by a trusted company (e.g. a telecommunications company). However, the massive use of mobile devices pave the way for the creation of ad hoc wireless networks that can be used to exchange information based on locations. When the exchange of location information is done amongst untrusted parties, the privacy of the participants could be in jeopardy. In this paper we present a novel solution that guarantees the privacy of the users of LBS. Our technique is built up of several modules that progressively increase the privacy level of the users. Unlike the existing approaches, our proposal does not rely on a trusted third party (TTP) to anonymise the users and to guarantee their location privacy.

Distributed controller design for open water channels

In the design of an automatic controller to achieve water-level set-point regulation and off-take load-disturbance rejection for an open water channel, a key concern is an inherent trade-off between local performance and the way water-level errors propagate due to control action. Here a structured optimal controller synthesis problem is formulated to systematically manage this trade-off, using H∞ loop-shaping ideas. The loop-shaping weights can be scalably designed and the imposed structure ensures the controller only involves local information exchange. Importantly, the distributed control structure we consider confines water-level error propagation to upstream pools, with corresponding benefits in terms of water distribution efficiency. Moreover, it coincides with the interconnection structure of a channel, and so the corresponding optimal synthesis problem has a convex characterisation; detailed state-space formulae are provided. Field test data are presented to illustrate overall performance.

Quorum and connected dominating sets based location service in wireless ad hoc, sensor and actuator networks

Location service provides position of mobile destination to source node to enable geo-routing. In existing quorum-based location service protocols, destination node registers its location along a ‘column’ while source node makes a query along a ‘row’. Grid and quorum-based location service is based on division of network into square grids, and selecting ‘leader’ location server node in each grid. Location updates, leader reelection and information transfer are performed whenever destination and leader nodes are moving to a different grid. We propose here to apply connected dominating sets (DS) as an alternative to grids. We also improved basic quorum, and applied on DS-quorum (DS based quorum) better criterion for triggering local information exchanges and global location updates, by meeting two criteria: certain distance movement and certain number of observed link changes with (DS) nodes. Backbones created by DS nodes (using 1-hop neighborhood information) are small size, do not have a parameter like grid size, and preserve network connectivity without the help of other nodes. Location updates and destination searches are restricted to backbone nodes. Both methods use ‘hello’ messages to learn neighbors. While this suffices to construct DS, grid leader (re)election requires additional messages. Simulation results show that using DS as backbone for quorum construction is superior to using grid as backbone or no backbone at all. The proposed DS-quorum location service can achieve higher (or similar) success rate with much less communication overhead than grid-based approaches.

An optimal coverage-preserving scheme for wireless sensor networks based on local information exchange

Coverage-preserving and energy-saving solutions have been reported in the literature and are generally based upon both quality coverage and off-duty scheme. Off-duty scheme based solutions present at least three challenging problems: (1) keeping coverage and connectivity of the network while optimizing the number of active sensor nodes; (2) resolving conflicts when determining which nodes should be turned off in order to save energy; and (3) finding optimal wake-up strategies that avoid waking up more nodes than necessary. This paper presents a novel distributed solution, the optimal coverage-preserving scheme (OCoPS), that extends the well-known Central Angle Method in order to identify fully sponsored nodes. OCoPS comprises an extended Central Angle Method, new decision algorithms devised to resolve the off-duty conflict problem under different network densities, and an energy-aware wake-up scheme that solves coverage hole problems in off-duty schemes. Compared to the widely used node scheduling scheme, our solution is based on local information exchange without the uncertainty of self-schedule algorithms. OCoPS is implemented as an extension of LEACH. A set of simulation experiments is carried out to evaluate its performance compared to other well-known schemes which are based on the Central Angle Method and self-scheduling. Our results indicate that on network lifetime OCoPS outperforms other schemes by over 20% and by over 25% when the coverage rate is higher than 80%. The experimental results also show that our coverage scheme effectively limits the number of on-duty node compared to the other schemes.

A MAC/Routing cross-layer approach to geographic forwarding in wireless sensor networks

Geographic forwarding is an emerging paradigm for communications between nodes in sensor networks. No exchange of location information is required, and nodes only have to know their own coordinates and those of the destination. Due to the device’s limited processing and storage capabilities, a simplified protocol architecture should be designed so as to make communications in these networks efficient and simple at the same time. Moreover, sensor nodes are battery supplied and, thus, protocol design should be aimed at reducing energy consumption in order to increase network lifetime. In this perspective, one sensor feature recently regarded as of key importance, is the ability to tune the transmission power. This allows the communication range to be varied according to node density and connectivity constraints. In this paper we propose an integrated cross-layer protocol, called MACRO, which integrates MAC and routing layer functionalities in order to support geographic forwarding in wireless sensor networks. In MACRO, a competition is triggered to select the best next relay node while forwarding information to the destination. The competition is based on the evaluation of a weighted progress factor representing the progress towards the destination per unit of transmission power. An analytical paradigm facilitating the most appropriate choice of the next relay is proposed. The proposed solution is assessed through both analysis and ns-2 simulations. Performance results show the advantages of the proposed solution when compared to other geographic forwarding protocols which do not exploit cross-layer features.