Central Solution Research Articles

Distributed energy trading on networked energy hubs under network constraints

A distributed energy trading scheme with non-discriminatory pricing for a cluster of networked energy hubs (NEHs) is proposed. First, each energy hub (EH) is treated as a self-interested agent. The hybrid AC/DC microgrid (MG)-embedded EH model is proposed to optimize the operating costs under corresponding local energy balance constraints. The supply limits of the input energy systems, e.g., electrical feeders and natural gas pipelines, are represented as the global coupling constraints among NEHs. Then, to obtain the optimal operation and trading strategies, the distributed energy trading is formulated as a generalized Nash game (GNG). To ensure the solubility of the GNG problem, the existence and uniqueness of the generalized Nash equilibrium (GNE) are proved. Furthermore, to transform the complexity of the solution, the multivariable GNG problem is reformulated as a N+1 Nash game (NG) without coupling constraints, the equivalence between NG and the solution set of variational inequality (VI) problem is established. Then, an efficient distributed projection-based algorithm is proposed to compute a Nash equilibrium (NE) for the NG problem. Finally, a potential game-based centralized solution method is also implemented as a baseline, and the comparison of simulation results demonstrates the effectiveness of our proposed algorithm.

Asynchronous telemedicine for clinical genetics consultations in the NICU: a single center's solution.

Many infants in the neonatal intensive care unit (NICU) have genetic disorders or birth defects. The demand for genetic services is often complicated by a shortage of genetic providers. Our hospital experienced a significant reduction in genetic workforce, leading to insufficient genetic services to meet demand. The Plan-Do-Study-Act method of quality improvement was used to assess available resources, select an intervention plan, and collect patient outcome and provider satisfaction data. An asynchronous telehealth model was deployed for clinical genetics consultations in our NICU utilizing a remote clinical geneticist. The pilot study included 111 asynchronous telehealth consultations; 21% received a genetic diagnosis before discharge. Diagnoses were primarily chromosomal and single gene disorders. Referring NICU providers reported high satisfaction. Asynchronous telehealth for clinical genetics is a feasible and successful alternative to an on-site clinical geneticist and should be considered in areas with a genetic workforce shortage.

Distributed Joint Power, Association and Flight Control for Massive-MIMO Self-Organizing Flying Drones

This article studies distributed algorithms to control self-organizing flying drones with massive MIMO networking capabilities - a network scenario referred to as mDroneNet . We attempt to answer the following fundamental question: what is the optimal way to provide spectrally-efficient wireless access to a multitude of ground nodes with mobile hotspots mounted on drones and endowed with a large number of antennas; when we can control the position of the drone hotspots, the association between the ground users and the drone hotspots, as well as the pilot sequence assignment and transmit power for the ground users? To the best of our knowledge, this is the first time that massive MIMO capabilities are considered in self-organizing flying drone networks. We first derive a mathematical formulation of the problem of joint power, association and movement control in mDroneNet, with the objective of maximizing the aggregate spectral efficiency of the ground users. It is shown that the resulting network control problem is a mixed integer nonlinear nonconvex programming (MINLP) problem. Then, a distributed solution algorithm with polynomial time complexity is designed by solving three closely-coupled subproblems: access association, joint pilot sequence assignment and power control, and drone movement control. As a performance benchmark, a globally-optimal but centralized solution algorithm is also designed based on a combination of the branch and bound framework and convex relaxation techniques. Results indicate that the distributed solution algorithm converges fast (within tens of iterations) and achieves a network spectral efficiency very close to the global optimum obtained by the centralized solution algorithm (over 90% in average).

Federated User Account Management

BNL SDCC (Scientific Data and Computing Center) recently deployed a centralized identity management solution to support Single Sign On (SSO) authentication across multiple IT systems. The system supports federated login access via CILogon and InCommon and multi-factor authentication (MFA) to meet security standards for various application and services such as Jupyterhub / Invenio that are provided to the SDCC user community. CoManage (cloud-based) and FreeIPA / Keycloak (local) are utilized to provided complex authorization for authenticated users. This talk will focus on technical overviews and strategies to tackle the challenges/obstacles in our facility.

Energy Efficient Spectrum Allocation and Mode Selection for D2D Communications in Heterogeneous Networks

In this paper, we consider a heterogeneous network consisting of both macro Base Station (MBS) and pico Base Stations (PBSs) in order to provide a spectrum allocation and mode selection in device-to-device (D2D) communications. A number of Component Carriers (CC) are considered available for allocation to the MBS and PBSs that are being utilized through carrier aggregation (CA) while mode selection decisions are made by each BS in order to balance between power consumption minimization and UE data rate requirements. A power minimization (energy-efficient) problem is formulated in order to provide a joint spectrum allocation and mode selection solution. This problem is solved using a state of the art optimization method known as proximal algorithm. First, a non-cooperative (centralized) solution is provided and second, a cooperative (distributed) employing distributed proximal algorithm is devised reducing the induced complexity. The cooperative solution is achieved by implementing distributed alternating direction method of multipliers (D-ADMM). Simulation results are carried out for all cases that reveal the energy efficient spectrum allocation and mode selection according under certain channels’ conditions that can balance between achieving high data rate requirements and power minimization. Finally, useful insights are presented such as complexity, convergence, delay and actual implementation of such a solution for the future wireless networks.

Comparison of Fusions Under Unknown and Partially Known Correlations

Abstract Approaches to decentralised estimation seek balance between proximity to the optimal centralised solution and complexity of the designed solution. Fusion of two estimates is a fundamental technique. Since unknown cross-correlation of estimation errors induces a loose evaluation of the fused estimate quality, a partial knowledge of correlations is beneficial. This paper inspects a recently introduced type of an implicit partial knowledge. The implicit knowledge is compared with other types of the knowledge in terms of families of upper bounds of mean square error (MSE) matrices. Next, an existence of a non-trivial lower bound of MSE matrices is discovered. Finally, the analytical results are illustrated graphically.

Transmit power and bits/channel use adaption in competitive cognitive radio networks

In this paper, we propose an optimization framework to determine the distribution of power and bits/channel use to secondary users in a competitive cognitive radio networks. The objectives of the optimization framework are to minimize total transmission power, maximize total bits/channel use and also to maintain quality of service. An upper bound on probability of bit error and lower bound on bits/channel use requirement of secondary users are considered as quality of service. The optimization problem is also constrained by total power budget across channels for a user. Simulating the framework in a centralized manner shows that more transmit power is required to allocate in a channel with higher noise power. However, allocation of bits/channel use is directly proportional to signal to interference plus noise power ratio. The proposed framework is more capable of supporting high bits/channel use requirement than existing resource allocation framework. We also develop the game theoretic user based distributed approach of the proposed framework. We see that user based distributed solution also follows centralized solution.

Distributed Workload Dissemination for Makespan Minimization in Disruption Tolerant Networks

Mobile devices are undergoing explosive proliferation today. Although they are gaining more and more capabilities, they still fall short to execute complex applications. One possible solution to alleviate this limitation is offloading tasks to remote clouds. However, it may require persistent connectivity to the Internet and thus is not always available or affordable. An alternative solution is taking advantage of pervasive mobile devices and their pairwise encounters. In this paradigm, complex tasks from mobile devices are processed in a distributed and collaborative fashion on all mobile devices that are loosely-connected. Working towards this vision, this paper studies the following problem: given a task that originates at some node in a Disruption Tolerant Network (DTN), how are we to disseminate the task's workload during the pairwise contacts among mobile devices to achieve makespan minimization? We first imagine access to an oracle that has global and future knowledge of node mobility, and we design a provably-optimal centralized polynomial-time solution as the benchmark for comparison. With the insights obtained from the centralized solution, we then develop a distributed dissemination algorithm, $\mathsf{D2}$ , which maintains certain neighborhood information at individual nodes. $\mathsf{D2}$ makes dissemination decisions based on the estimations of the potential computational capacities and the future workloads of mobile nodes. Extensive trace-driven simulations confirm the effectiveness of $\mathsf{D2}$ .

To Transmit or Not to Transmit? Distributed Queueing Games in Infrastructureless Wireless Networks

We study distributed queueing games in interference-limited wireless networks. We formulate the throughput maximization problem via distributed selection of users' transmission thresholds as a Nash Equilibrium Problem (NEP). We first focus on the solution analysis of the NEP and derive sufficient conditions for the existence and uniqueness of a Nash Equilibrium (NE). Then, we develop a general best-response-based algorithmic framework wherein the users can explicitly choose the degree of desired cooperation and signaling, converging to different types of solutions, namely: 1) a NE of the NEP when there is no cooperation among users and 2) a stationary point of the Network Utility Maximization (NUM) problem associated with the NEP, when some cooperation among the users in the form of (pricing) message passing is allowed. Finally, as a benchmark, we design a globally optimal but centralized solution method for the nonconvex NUM problem. Our experiments show that in many scenarios the sum-throughput at the NE of the NEP is very close to the global optimum of the NUM problem, which validates our noncooperative and distributed approach. When the gap of the NE from the global optimality is non negligible (e.g., in the presence of high coupling among users), exploiting cooperation among the users in the form of pricing enhances the system performance.

Devolution and grant-in-aid design for the provision of impure public goods.

Traditional fiscal federalism theory postulates that devolution for the provision of local public goods increases welfare. However, most of the services offered at local level are local impure public goods whose characteristics may prevent devolution from being efficient. Our paper shows that devolution is the optimal choice only for local impure public goods. For an environment characterised by coordination and asymmetry of information problems, we propose the optimal grants-in-aid formula that Central Government should use to reduce welfare losses and we compare it with what suggested by the mainstream literature. Finally, we show under which conditions devolution should be preferred to a centralised solution. From a policy point of view, our paper may explain the heterogeneity in the choices made by countries in terms of devolution in the provision of merit and impure public goods.

Exploring the optimal substream scheduling and distribution mechanism for data-driven P2P media streaming

Most P2P live streaming systems divide video stream into fine-grained blocks, and paralleled distribute these blocks in overlay network to utilize the bandwidth and storage resources of end users, which improves the scalability. Although transmitting video stream with these blocks greatly guarantees the system robustness, it also brings long distribution delay and high protocol overhead issues. Therefore, aggregating these blocks to substreams and delivering them in data-driven mode can promote the distribution efficiency under the network environment with peer churn. In this paper, we study the substream scheduling and distribution mechanism in data-driven overlay network, and formulate it as a minimax problem. Subsequently, we propose a global centralized approach to solve this problem, and derive the optimal substream scheduling and distribution scheme. According to the design idea of global centralized solution, we present a distributed substream scheduling and distribution mechanism, which is adaptive to dynamic P2P network. Finally, we compare the performance of global centralized solution and distributed substream scheduling and distribution mechanism with block-based live streaming. The experiment results show substream-based design achieves better efficiency in video stream dissemination, and distributed substream scheduling and distribution mechanism can preserve high performance when peer churn appears.

SMS Based Monitoring System of TV Transmitting Station

According to the requirements of remote monitoring for TV transmitting station, present a SMS based centralized monitoring solution. In this solution, the GSM network and Ethernet was combined together, and remote monitoring was achieved through GSM short message service. Introduced the total structure of the system, described the software designs of the device agent and the message server, as well as the communication protocols between each components.

Dynamic decentralised algorithms for cognitive radio relay networks with multiple primary and secondary users utilising matching theory

ABSTRACTWe propose a distributed spectrum access algorithm for cognitive radio relay networks with multiple primary users (PUs) and multiple secondary users (SUs). The key idea behind the proposed algorithm is that the PUs negotiate with the SUs on both the amount of monetary compensation, and the amount of time the SUs are either (i) allowed spectrum access, or (ii) cooperatively relaying the PU's data, such that both the PUs' and the SUs' minimum rate requirements are satisfied. The proposed algorithm is shown to be flexible in prioritising either the PUs or the SUs. We prove that the proposed algorithm will result in the best possible stable matching and is weak Pareto optimal. Numerical analysis also reveals that the distributed algorithm can achieve a performance comparable to an optimal centralised solution, but with significantly less overhead and complexity. Copyright © 2013 John Wiley & Sons, Ltd.

A new CDF model for data movement based on SRM

Being a large international collaboration established well before the full development of the Grid as the main computing tool for High Energy Physics, CDF has recently changed and improved its computing model, decentralizing some parts of it in order to be able to exploit the rising number of distributed resources available nowadays. Despite those efforts, while the large majority of CDF Monte Carlo production has moved to the Grid, data processing is still mainly performed in dedicated farms hosted at FNAL, requiring a centralized management of data and Monte Carlo samples needed for physics analysis. This rises the question on how to manage the transfer of produced Monte Carlo samples from remote Grid sites to FNAL in an efficient way; up to now CDF has relied on a non scalable centralized solution based on dedicated data servers accessed through rcp protocol, which has proven to be unsatisfactory. A new data transfer model has been designed that uses SRMs as local caches for remote Monte Carlo production sites, interfaces them with SAM, the experiment data catalog, and finally realizes the file movement exploiting the features provided by the data catalog transfer layer. We describe here the model and its integration within the current CDF computing architecture.

Distributed transmit power allocation for multihop cognitive-radio systems

In this paper, we consider a relay-assisted wideband cognitive-radio (CR) system under the assumption that the frequency band chosen by the CR relay network for unlicensed spectrum usage overlaps with one or more bands dedicated to primary (e.g., licensed) narrowband links. Our objective is to optimize the performance of the CR system while limiting the interference in direction of the primary receivers, without requiring any adaptation of the transmitted signal spectra at the cognitive nodes. To this end, we study appropriate transmit power allocation (TPA) strategies among the cognitive relays. We first investigate the optimal centralized (OC) TPA solution and show that it can be formulated as a linear program. Since the OC-TPA solution requires a considerable amount of information exchange between the cognitive nodes, we develop two distributed TPA schemes, namely (i) a fully decentralized (FD) TPA scheme and (ii) a distributed feedback-assisted (DFA) TPA scheme. The FD-TPA scheme aims at maximizing the output signal-to-interference- plus-noise ratio (SINR) at the destination node of the CR network according to a best-effort strategy. It requires neither feedback information from the destination node nor an exchange of channel state information between the cognitive relays. The DFA-TPA scheme, on the other hand, utilizes feedback information from the destination node, in order to achieve a predefined target output SINR value, while minimizing the overall transmit power spent by the relays. Analytical and simulation-based performance results illustrate that notable performance improvements compared to non-cooperative transmission (i.e., without relay assistance) are achieved by the proposed schemes, especially when more than two hops are considered. In particular, the proposed distributed TPA schemes typically perform close to the OC-TPA solution.

Analysis of Line Monitoring Device Network using Centralized Failure Troubleshooting System

An optical time domain reflectometer (OTDR) is an instrument that used to measure parameters such as attenuation, length, connectors and splice losses, reflectance level and locating faults in an optical link. The measurement results are saved in OTDR and then transfer into computer for further analysis by using computer-based emulation software for performing more OTDR trace processing. In this paper, we proposed and demonstrated a new in-line monitoring and testing system based on Line Monitoring Device (LMD) and Centralized Failure Detection System (CFDS) for transmission surveillance and failure detection without affecting the transmission in an optical access network. LMD is passive device for optical signals tapping purpose; meanwhile CFDS is a centralized monitoring and troubleshooting solution with the GUI processing in MATLAB software. The LMD network will be analysis through both programs by means of OTDR installed software and our CFDS. The results are eventually compared and show both are reliable with the second is able to be extended for further analysis. Any fiber failure or breakdown occurs in the network will be determined by CFDS while the LMD is used to determine sharply the point of failure before it is been repaired. The proposed systems are able to improve the service reliability and reduce the repairing cost and time.

Game theory and power control in ultrawideband networks

This paper describes a theoretical framework for the design and analysis of power control algorithms for high-throughput wireless networks using ultrawideband (UWB) technologies. The tools of game theory are shown to be expedient for deriving scalable, energy-efficient, distributed power control schemes to be applied to a population of battery-operated user terminals in a rich multipath environment. In particular, the power control issue is modeled as a dynamic noncooperative game in which each user chooses its transmit power so as to maximize its own utility, which is defined as the ratio of throughput to transmit power. Although distributed (noncooperative) control is known to be suboptimal with respect to the optimal centralized (cooperative) solution, it is shown via large-system analysis that the game-theoretic distributed algorithm based on Nash equilibrium exhibits negligible performance degradation with respect to the centralized socially optimal configuration. The framework described here is general enough to also encompass the analysis of code division multiple access (CDMA) systems and to show that UWB slightly outperforms CDMA in terms of achieved utility at the Nash equilibrium.

Bottlenecks in name resolution of migrating processes

Three naming strategies are discussed that allow the processes of a distributed application to continue being addressed by their original logical name, along all the migrations they may be forced to undertake because of performance-improvement goals. A simple centralised solution is firstly discussed which showed a software bottleneck with the increase of the number of processes; other two solutions are considered that entail different communication schemes and different communication overheads for the naming protocol. All these strategies are based on the facility that each process is allowed to survive after migration, even in its original site, only to provide a forwarding service to those communications that used its obsolete address.