Efficient user-channel pairing with power-domain sum-rate maximization in opportunistic hybrid OFDMA-NOMA IoT systems

Non-orthogonal multiple access (NOMA) along with cognitive radio (CR) have been recently configured as potential solutions to fulfill the extraordinary demands of the fifth generation (5G) and beyond (B5G) networks and support the Internet of Thing (IoT) applications. Multiple users can be served within the same orthogonal domains in NOMA via power-domain multiplexing, whilst CR allows secondary users (SUs) to access the licensed spectrum frequency. This work investigates the possibility of combining orthogonal frequency division multiple access (OFDMA), NOMA, and CR, referred to as hybrid OFDMA-NOMA CR network. With this hybrid technology, the licensed frequency is divided into several channels, such as a group SUs is served in each channel based on NOMA technology. In particular, a rate-maximization framework is developed, at which user pairing at each channel, power allocations for each user, and secondary users activities are jointly considered to maximize the sum-rate of the hybrid OFDMA-NOMA CR network, while maintaining a set of relevant NOMA and CR constraints. The developed sum-rate maximization framework is NP-hard problem, and cannot be solved through classical approaches. Accordingly, we propose a two-stage approach; in the first stage, we propose a novel user pairing algorithm. With this, an iterative algorithm based on the sequential convex approximation is proposed to evaluate the solution of the non-convex rate-maximization problem, in the second stage. Results show that our proposed algorithm outperforms the existing schemes, and CR network features play a major role in deciding the overall network’s performance.

     

Resource Management for Ad-Hoc Wireless Networks with Cluster Organization

Boosted by technology advancements, government and commercial interest, ad-hoc wireless networks are emerging as a serious platform for distributed mission-critical applications. Guaranteeing QoS in this environment is a hard problem because several applications may share the same resources in the network, and mobile ad-hoc wireless networks (MANETs) typically exhibit high variability in network topology and communication quality. In this paper we introduce DYNAMIQUE, a resource management infrastructure for MANETs. We present a resource model for multi-application admission control that optimizes the application admission utility, defined as a combination of the QoS satisfaction ratio. A method based on external adaptation (shrinking QoS for existing applications and later QoS expansion) is introduced as a way to reduce computation complexity by reducing the search space. We designed an application admission protocol that uses a greedy heuristic to improve application utility. For this, the admission control considers network topology information from the routing layer. Specifically, the admission protocol takes benefit from a cluster network organization, as defined by ad-hoc routing protocols such as CBRP and LANMAR. Information on cluster membership and cluster head elections allows the admission protocol to minimize control signaling and to improve application quality by localizing task mapping.     

Quality of care in unlicensed homes for the aged in the Eastern Townships of Quebec

BACKGROUND: The recent proliferation of unlicensed homes for the aged in Quebec, coupled with the increased needs of the population they serve, has raised concerns about the quality of case these homes provide. The authors compared the quality of care in unlicensed homes with that in licensed long-term care facilities in a region of Quebec. METHODS: The study involved 301 impaired people aged 65 and over in 88 residential care facilities (52 unlicensed, 36 licensed) in the Eastern Townships of Quebec. Study participants were chosen according to a 2-stage sampling scheme: stratified sampling of the primary units (facilities) and random sampling of the secondary units (residents). Quality of care was measured using the QUALCARE scale, a multidimensional instrument that uses a 5-point scale to assess 6 dimensions of care: environmental, physical, medical management, psychosocial, human rights and financial. A mean score of more than 2 was considered indicative of inadequate care. RESULTS: Overall, the quality of care was similar in the unlicensed and licensed facilities (mean global score 1.61 [standard error of the mean (SEM) 0.06] and 1.47 [SEM 0.09] respectively). Examination of dimension-specific quality-of-care scores revealed that the unlicensed homes performed worse than the licensed facilities in 2 areas of care: physical care (mean score 1.80 [SEM 0.08] v. 1.51 [SEM 0.09] respectively, p = 0.017) and medical management (1.37 [SEM 0.06] v. 1.14 [SEM 0.05], p = 0.004). The dimension-specific scores also revealed that both types of homes lacked appropriate attention to the psychosocial aspect of care. Overall, 25% of the facilities provided inadequate care to at least one resident. This situation was especially prevalent among homes with fewer than 40 residents, where up to 20% of the residents received inadequate care. INTERPRETATION: Most of the unlicensed homes for the aged that were studied delivered care of relatively good quality. However, some clearly provided inadequate care.     

Two Monthly Continuous Dynamic Model Based on Nash Bargaining Theory for Conflict Resolution in Reservoir System

So far many optimization models based on Nash Bargaining Theory associated with reservoir operation have been developed. Most of them have aimed to provide practical and efficient solutions for water allocation in order to alleviate conflicts among water users. These models can be discussed from two viewpoints: (i) having a discrete nature; and (ii) working on an annual basis. Although discrete dynamic game models provide appropriate reservoir operator policies, their discretization of variables increases the run time and causes dimensionality problems. In this study, two monthly based non-discrete optimization models based on the Nash Bargaining Solution are developed for a reservoir system. In the first model, based on constrained state formulation, the first and second moments (mean and variance) of the state variable (water level in the reservoir) is calculated. Using moment equations as the constraint, the long-term utility of the reservoir manager and water users are optimized. The second model is a dynamic approach structured based on continuous state Markov decision models. The corresponding solution based on the collocation method is structured for a reservoir system. In this model, the reward function is defined based on the Nash Bargaining Solution. Indeed, it is used to yield equilibrium in every proper sub-game, thereby satisfying the Markov perfect equilibrium. Both approaches are applicable for water allocation in arid and semi-arid regions. A case study was carried out at the Zayandeh-Rud river basin located in central Iran to identify the effectiveness of the presented methods. The results are compared with the results of an annual form of dynamic game, a classical stochastic dynamic programming model (e.g. Bayesian Stochastic Dynamic Programming model, BSDP), and a discrete stochastic dynamic game model (PSDNG). By comparing the results of alternative methods, it is shown that both models are capable of tackling conflict issues in water allocation in situations of water scarcity properly. Also, comparing the annual dynamic game models, the presented models result in superior results in practice. Furthermore, unlike discrete dynamic game models, the presented models can significantly reduce the runtime thereby avoiding dimensionality problems.     

SaMW: a probabilistic meta-heuristic algorithm for job scheduling in heterogeneous distributed systems powered by microservices

Cluster Computing - Applications are evolving in ways that demand geographically distributed resources to co-operate in order to give users better Quality of Service (QoS). There is a plethora of...     

Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction

One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer’s utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.     

Dynamic Quality of Service Model for Improving Performance of Multimedia Real-Time Transmission in Industrial Networks

Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.     

Enabling greener DSL access networks by their stabilization with artificial noise and SNR margin

Low-power modes (LPM) are a standardized means in asymmetric digital subscriber lines (ADSL) 2 for reducing the power consumption at the central office. However, the activation of LPMs is hampered by the operators’ concern for instability introduced by frequent transmit power changes. The injection of artificial noise (AN) has been proposed as a standard-compliant stabilization technique. We develop an analytical solution for setting the AN power spectrum. Based on this solution we jointly optimize the AN power spectrum and the signal-to-noise ratio (SNR) margin. Simulation results show the performance gain in terms of rate and energy compared to heuristic rules for setting the AN power spectrum. We propose and demonstrate three approaches for evaluating the performance of AN-enabled DSL systems, including (a) joint spectrum balancing, AN, and margin optimization, (b) single-user worst-case-stable optimization, and (c) worst-case-stable optimization based on sequential initialization. Simulation results confirm a strong dependency of the performance under AN on the selected SNR margins, and highlight the total AN power consumption as well as the residual energy savings under low-power modes stabilized by AN.     

Dynamic decision-making in uncertain environments I. The principle of dynamic utility

Understanding the dynamics or sequences of animal behavior usually involves the application of either dynamic programming or stochastic control methodologies. A difficulty of dynamic programming lies in interpreting numerical output, whereas even relatively simple models of stochastic control are notoriously difficult to solve. Here we develop the theory of dynamic decision-making under probabilistic conditions and risks, assuming individual growth rates of body size are expressed as a simple stochastic process. From our analyses we then derive the optimization of dynamic utility, in which the utility of weight gain, given the current body size, is a logarithmic function: hence the fitness function of an individual varies depending on its current body size. The dynamic utility function also shows that animals are universally sensitive to risk and display risk-averse behaviors. Our result proves the traditional use of expected utility theory and game theory in behavioral studies is valid only as a static model.     

Object-Oriented Design of QoS Multicast Communications

Multicast (group) communications have been widely recognized by current research and industry. Multicast is very useful for various network applications such as distributed (replicated) database, video/audio conference, information distribution and server locations, etc. But design and implementation of such multicast communication systems in networks are complicated tasks, especially when quality of services (QoS) of applications such as real-time and reliability are desired. To quick design and implement multicast communication, good tools are crucial and must be facilitated. This paper presents a novel object-oriented (O-O) QoS driven approach for the quick design and prototyping of multicast communication systems under certain QoS requirements for multicast message transmission and receptions such as real-time, total ordering, atomicity and fault-tolerance, etc.     

Replication of Nuclei from Cycling and Quiescent Mammalian Cells in 6-DMAP-TreatedXenopusEgg Extract

Nuclear membrane permeabilization is required for replication of quiescent (G0) cell nuclei inXenopusegg extract. We now demonstrate that establishment of replication competence in G0 nuclei is dependent upon a positive activity present in the soluble egg extract. Our hypothesis is that G0 nuclei lose the license to replicate following growth arrest and that this positive activity is required for relicensing DNA for replication. To determine if G0 nuclei contain licensed DNA, we used the protein kinase inhibitor, 6-dimethylaminopurine (6-DMAP), to prepare egg extracts that are devoid of licensing activity. Intact nuclei, isolated from mammalian cells synchronized in G1-phase (licensed), G2-phase (unlicensed), and G0 were permeabilized and assayed for replication in 6-DMAP-treated and untreated extracts supplemented with [α-³²P]dATP or biotinylated-dUTP. Very little radioactivity was incorporated into nascent DNA in each nuclear population; however, nearly all nuclei in each population incorporated biotin in 6-DMAP extract. The pattern of biotin incorporation within these nuclei was strikingly similar to the punctate pattern observed within nuclei incubated in aphidicolin-treated extract, suggesting that initiation events occur within most replication factories in 6-DMAP extract. However, density substitution and alkaline gel analyses indicate that the incorporated biotin within these nuclei arises from a small number of active origins which escape 6-DMAP inhibition. We conclude that 6-DMAP-treated egg extract cannot differentiate licensed from unlicensed mammalian somatic cell nuclei and, therefore, cannot be used to determine the “licensed state” of G0 nuclei using the assays described here.     

The slow process: A hypothetical cognitive adaptation for distributed cognitive networks

Human cognitive evolution is characterized by two special features that are truly novel in the primate line. The first is the emergence of "mindsharing" cultures that perform cooperative cognitive work, and serve as distributed cognitive networks. The second is the emergence of a brain that is specifically adapted for functioning within those distributed networks, and cannot realize its design potential without them. This paper proposes a hypothetical neural process at the core of this brain adaptation, called the "slow process". It enables the human brain to comprehend social events of much longer duration and complexity than those that characterize primate social life. It runs in the background of human cognitive life, with the faster moving sensorimotor interface running in the foreground. Most mammals can integrate events in the shorter time zone that corresponds to working memory. However, very few can comprehend complex events that extend over several hours (for example, a game or conversation) in what may be called the "intermediate" time zone. Adult humans typically live, plan, and imagine their lives in this time range, which seems to exceed the capabilities of our closest relatives, bonobos and chimpanzees. In summary, human cognition has both an individual and a collective dimension. Individual brains and minds function within cognitive-cultural networks, or CCNs, that store and transmit knowledge. The human brain relies on cultural input even to develop the basic cognitive capacities needed to gain access to that knowledge in the first place. The postulated slow process is a top-down executive capacity that evolved specifically to manage the cultural connection, and handle the cognitive demands imposed by increasingly complex distributed systems.     

Understanding autonomic sympathovagal balance from short-term heart rate variations. Are we analyzing noise?

Heart rate variations reflect the output of the complex control of the heart mediated by the autonomic nervous system. Because of that, they also encode different types of information, namely the efferent outflow of reflex mechanisms involved in the beat-to-beat control of cardiac function, the efferent activity of neurohumoral elements involved in the control of other cardiovascular parameters and random noise resulting from the hysteresis of the different controllers. The degree to which power spectrum estimation methods will uncover the periodic component of heart rate variations is in direct relation with the status of the system under study. Although the utility of spectral methods is now established in mammalian research, very little is known on the utility of these techniques in non-mammalian cardiovascular research. This review covers this space by discussing the physiological significance of heart rate variations in non-mammalian vertebrates. A detailed account of the different steps of the technique, its limitations and the ways to overcome these problems are also presented. These are: the recording of the cardiac event signal, the detection and digital processing methods, the satisfaction of stationarity conditions, the problem of spectral leakage and the different methods to estimate the power spectrum.     

A General Scheme to Predict Partner Control Mechanisms in Pairwise Cooperative Interactions Between Unrelated Individuals

Recent years have seen an explosion in the diversity of partner control mechanisms hypothesised to stabilise cooperative behaviour among unrelated individuals. Game theory suggests numerous strategies, each with specific decision rules that allow cooperators to control a non‐contributing partner. This diversity of hypothetical strategies seems likely to reflect diversity in the types of intraspecific cooperation and interspecific mutualism that exist in nature. It is therefore important to provide a framework that explains similarities and differences between the various hypothetical strategies and that predicts how key parameters that describe the natural history of natural systems favour different control mechanisms. We develop a novel unifying framework for pairwise interactions between unrelated individuals, in which we link specific control mechanisms to specific game structures. The latter are defined by unique combinations of the states of five parameters that describe investment, aspects of the payoff matrix, the number of interactions and partner choice. We find that specific control mechanisms potentially have utility in a limited number of game structures; conversely, each game structure may typically offer a few competing control mechanisms. Our framework offers theoreticians specific problems that await mathematical exploration, while at the same time offering empiricists guidelines for evaluating the game structure and corresponding control mechanisms in their systems.     

An adaptive dual control framework for QoS design

The widespread deployment of the advanced computer technology in business and industries has demanded the high standard on quality of service (QoS). For example, many Internet applications, i.e. online trading, e-commerce, and real-time databases, etc., execute in an unpredictable general-purpose environment but require performance guarantees. Failure to meet performance specifications may result in losing business or liability violations. As systems become distributed and complex, it has become a challenge for QoS design. The ability of on-line identification and auto-tuning of adaptive control systems has made the adaptive control theoretical design an attractive approach for QoS design. However, there is an inherent constraint in adaptive control systems, i.e. a conflict between asymptotically good control and asymptotically good on-line identification. This paper first identifies and analyzes the limitations of adaptive control for network QoS by extensive simulation studies. Secondly, as an approach to mitigate the limitations, we propose an adaptive dual control framework. By incorporating the existing uncertainty of on-line prediction into the control strategy and accelerating the parameter estimation process, the adaptive dual control framework optimizes the tradeoff between the control goal and the uncertainty, and demonstrates robust and cautious behavior. The experimental study shows that the adaptive dual control framework mitigate the limitations of the conventional adaptive control framework. Compared with the conventional adaptive control framework under the medium uncertainty, the adaptive dual control framework reduces the deviation from the desired hit-rate ratio from 40% to 13%.

PGTrust: a decentralized free-riding prevention model for DG systems

Desktop grids (DG) offer large amounts of computing power coming from internet-based volunteer networks. They suffer from the free-riding phenomenon. It may be possible for users to free ride, consuming resources donated by others but not donating any of their own. In this paper, we present PGTrust: our decentralized free-riding prevention model designed for PastryGrid. PastryGrid is a decentralized DG system which manages resources over a decentralized P2P network. PGTrust relies on the notion of score which is a metric of reputation used to evaluate the level of QoS of a peer. We have conducted out experimentations on Grid’5000 testbed. Obtained results prove the benefits of our free-riding prevention model. PGTrust is able to improve application running time by discouraging free-riders and motivating selfish peers to contribute. It offers a considerable speedup over distributed applications.     

Incorporating service and user information and latent features to predict QoS for selecting and recommending cloud service compositions

The rapid growth of published cloud services in the Internet makes the service selection and recommendation a challenging task for both users and service providers. In cloud environments, software re services collaborate with other complementary services to provide complete solutions to end users. The service selection is performed based on QoS requirements submitted by end users. Software providers alone cannot guarantee users’ QoS requirements. These requirements must be end-to-end, representing all collaborating services in a cloud solution. In this paper, we propose a prediction model to compute end-to-end QoS values for vertically composed services which are composed of three types of cloud services: software (SaaS), infrastructure (IaaS) and data (DaaS) services. These values can be used during the service selection and recommendation process. Our model exploits historical QoS values and cloud service and user information to predict unknown end-to-end QoS values of composite services. The experiments demonstrate that our proposed model outperforms other prediction models in terms of the prediction accuracy. We also study the impact of different parameters on the prediction results. In the experiments, we used real cloud services’ QoS data collected using our developed QoS monitoring and collecting system.