Resource Congestion Research Articles

THE EQUALITY NORM MEETS THE EVOLUTION OF PROPERTY IN THE LAW OF “TAKINGS”

Abstract:A norm of equal treatment is cited regularly in the American jurisprudence of property “takings” under the Fifth and Fourteenth Amendments to the Constitution, as a benchmark of fair treatment of owners. According to an increasingly prevalent version of this equality norm, courts should look to parity of treatment among property owners in investigating whether particular regulations “take” property. This essay argues, however, that such an equality norm is misplaced, and that courts should judge fairness by the criterion of expectation—including reasonable expectations of regulation.A norm of equality becomes problematic in the face of the economic theory of the evolution of property. This theory posits that as resources become more congested, their uses carry increasing common pool costs or “externalities”—a scenario that should predictably result in more stringent resource management—up to and including the establishment of regulatory regimes as well as property rights themselves. This evolutionary pattern, however, places earlier and later resource users in different positions vis-à-vis both common pool externalities and regulatory responses, and their different temporal positions fragment the meaning of equal treatment and destabilize it as a jurisprudential norm. This essay argues that while equal treatment may be a benchmark for special or invidious cases, like those relating to civil rights, the great bulk of takings cases involve regulatory responses to congesting resources, where a norm of equal treatment breaks down. Thus, in seeking fair treatment, takings jurisprudence should downplay equality and instead look to the understanding of property as a basis of expectations—but those expectations should include the anticipation of reasonable regulatory responses to resource congestion.

Should Congestion Tolls be Set by the Government or by the Private Sector? The Knight–Pigou Debate Revisited

This paper clarifies issues debated by A. C. Pigou and Frank Knight about correcting inefficient use of congestible resources, focusing for concreteness on their original example of road congestion. Instead of government‐imposed Pigouvian access fees, Knight favoured access fees set by private toll‐setters. We consider the case of n≥2 congestible roads and an uncongestible road of arbitrary speed. Knight argued that in the case of a single congestible road, a private toll‐setter would always choose the toll that Pigou recommended, hence the allocation would minimize aggregate commute time without government meddling. We find instead that two or more toll‐setters would never choose Pigouvian tolls except in the special case of a sufficiently fast uncongestible road. Moreover, for uncongestible roads of slower speed, the allocation of motorists under Knight's proposal is almost never efficient. Whenever it is inefficient, motorists are strictly worse off when they pay tolls set by private firms instead of paying government‐imposed tolls, and aggregate toll revenue is also lower. Nevertheless, if the private sector does set tolls, then the full cost to motorists can be limited if the government provides an uncongestible alternative, such as a train, to offer potential competition along the same route.

Efficient polling cycle adaptive passive optical network for low-latency 5G fronthaul

Under the large and ubiquitous bandwidth requirements of the upcoming 5G era, new common public radio interface (CPRI) solutions (such as eCPRI) characterized by scale flexible, packet-based bandwidth reduction are receiving extensive attention. In this context, applying a passive optical network (PON) into the mobile fronthaul (MFH) has good prospects due to the features of low cost and wide coverage. However, the millisecond-level latency of the dynamic bandwidth allocation (DBA) procedure exceeds the harsh latency constraints of 5G MFH, and the uneven distribution of traffic caused by user mobility brings waste or congestion of MFH bandwidth resources. To meet the latency constraint and simultaneously improve bandwidth utilization, we propose a flexible time- and wavelength-division multiplexed passive optical network (TWDM-PON)-based MFH architecture, in which optical network units (ONUs) can be dynamically grouped to support efficient use of the bandwidth and adaptive polling cycle. Based on this architecture, the influence of the propagation time on latency is analyzed, and a joint bandwidth and latency constraint (JBL) grouping algorithm is proposed to obtain the appropriate ONU group for different network slice scenarios. The simulation results indicate that, in the case satisfying the latency constraint, the bandwidth utilization reaches 94% and above (maximum 99.5%). Simultaneously, within different slicing scenarios, the polling cycle can be increased by 98% on average (maximum 122%) or decreased by a maximum of 36μs. Compared with the non-grouping situation, the adaptive polling cycle lowers the performance requirement of the hardware device (such as a burst mode transmitter), expands the MFH coverage, and improves the channel utilization.

Software Defined Radio Implementation of a Digital Self-interference Cancellation Method for Inband Full-Duplex Radio Using Mobile Processors

New means to improve spectral efficiency and flexibility in radio spectrum use are in high demand due to congestion of the available spectral resources. Systems deploying inband full-duplex transmission aim at providing higher spectral efficiency by concurrent transmission and reception at the same frequency. Potentially doubling system throughput, full-duplex communications is considered as an enabler technology for the upcoming 5G networks. However, system performance is degraded due to the strong self-interference (SI) caused by overlapping of high power transmit signal with the received signal of interest. Furthermore, due to commonly existing radio frequency imperfections, advanced techniques capable of mitigating nonlinear SI are required. This article presents a real-time software-defined implementation of a digital SI canceller for full-duplex transceivers, potentially applicable even in mobile-scale devices. Recently, software-defined radio has gained a lot of interest due to its higher flexibility, scalability, and shorter time-to-market cycles compared to traditional fixed-function hardware designs. Moreover, as the performance enhancements achieved by increasing the clock frequency is reaching its limits, the current trend is towards multi-core processors. Since contemporary mobile phones already contain powerful massively parallel GPUs and CPUs, feasibility of a real-time implementation on mobile processors is studied. The reported results show that by adopting the presented solution, it is possible to achieve sufficient SI cancellation under time varying coupling channel conditions. Additionally, the possibility of carrying out such advanced processing in a real-time fashion on the selected platforms is investigated, and the implementation is evaluated in terms of execution time, power, and energy consumption.

Early miss prediction based periodic cache bypassing for high performance GPUs

The aim of the hierarchical cache memories that are equipped for GPUs is the management of irregular memory access patterns for general purpose workloads. The level-1 data cache (L1D) of the GPU plays an important role for its ability in the provision of high bandwidth and low-latency data accesses. Unfortunately, the GPU L1D may become a performance bottleneck due to facing many performance challenges such as cache contention and resource congestion. These critical issues come from a large number of simultaneous requests from the SIMT cores to the limited-capacity L1D. We observe that many applications have a large number of requests with a very low reuse probability, resulting in the GPU performance degradation. To overcome these challenges, we propose an efficient cache bypassing mechanism that can periodically filter the access stream and make an accurate bypassing decision to improve the efficiency of the L1D. The proposed technique uses a small storage amount to save the tag array of the L1D for the early miss prediction before it makes the bypassing decision. The experiment results reveal that the proposed technique significantly increases the cache efficiency and the GPU performance.

Dynamic Repositioning to Reduce Lost Demand in Bike Sharing Systems

Bike Sharing Systems (BSSs) are widely adopted in major cities of the world due to concerns associated with extensive private vehicle usage, namely, increased carbon emissions, traffic congestion and usage of nonrenewable resources. In a BSS, base stations are strategically placed throughout a city and each station is stocked with a pre-determined number of bikes at the beginning of the day. Customers hire the bikes from one station and return them at another station. Due to unpredictable movements of customers hiring bikes, there is either congestion (more than required) or starvation (fewer than required) of bikes at base stations. Existing data has shown that congestion/starvation is a common phenomenon that leads to a large number of unsatisfied customers resulting in a significant loss in customer demand. In order to tackle this problem, we propose an optimisation formulation to reposition bikes using vehicles while also considering the routes for vehicles and future expected demand. Furthermore, we contribute two approaches that rely on decomposability in the problem (bike repositioning and vehicle routing) and aggregation of base stations to reduce the computation time significantly. Finally, we demonstrate the utility of our approach by comparing against two benchmark approaches on two real-world data sets of bike sharing systems. These approaches are evaluated using a simulation where the movements of customers are generated from real-world data sets.

Analysis on pure e-commerce congestion effect, productivity effect and profitability in China

This paper examines the relationship of e-commerce congestion effect, productivity effect and profit generation in China. The technique of Data Envelopment Analysis (DEA) is used to measure returns to scale and total factor productivity in e-commerce. The results show that e-commerce firms achieve productivity growth but suffer from input congestion. Congestion weakens profitability and leads to negative returns of inputs to outputs. This finding offers a new insight to explain the determinants of profit change. This research enriches production theory of internet companies, and helps managers strengthen their profitability by measuring the existence of congestion and eliminating input congestion resources.

When is increasing consumption of common property optimal? Sorting, congestion and entry in the commons

First-best pricing or assignment of property rights for rival and non-excludable goods is often infeasible. In a setting where the social planner cannot limit total use, we show that common-property resources can be over or under-consumed. This depends on whether the external benefits of reallocating users to less congested resources outweigh the additional costs imposed by new entrants. Importantly, we show that it may be optimal to encourage consumption of some common property resources. Our results have important implications for settings ranging from fisheries and forestry to recreational demand and transportation.

Efficient Orchestration Mechanisms for Congestion Mitigation in NFV: Models and Algorithms

Network Functions Virtualization (NFV) has recently gained momentum among network operators as a means to share their physical infrastructure among virtual operators, which can independently compose and configure their communication services. However, the spatio-temporal correlation of traffic demands and computational loads can result in high congestion and low network performance for virtual operators, thus leading to service level agreement breaches. In this paper, we analyze the congestion resulting from the sharing of the physical infrastructure and propose innovative orchestration mechanisms based on both centralized and distributed approaches, aimed at unleashing the potential of the NFV technology. In particular, we first formulate the network functions composition problem as a non-linear optimization model to accurately capture the congestion of physical resources. To further simplify the network management, we also propose a dynamic pricing strategy of network resources, proving that the resulting system achieves a stable equilibrium in a completely distributed fashion, even when all virtual operators independently select their best network configuration. Numerical results show that the proposed approaches consistently reduce resource congestion. Furthermore, the distributed solution well approaches the performance that can be achieved using a centralized network orchestration system.

Maximizing social welfare in congestion games via redistribution

It is well known that efficient use of congestible resources can be achieved via marginal pricing; however, payments collected from the agents generate a budget surplus, which reduces social welfare. We show that an asymptotically first-best solution in the number of agents can be achieved by the appropriate redistribution of the budget surplus back to the agents.

Impacto de la demanda de un turismo social en la sustentabilidad de la actividad en el balneario de El Quisco, Provincia de San Antonio - Chile

Every summer Chile’s Central Coast undergoes the effects of social tourism, as a vast number of low-income visitors arrive from Chile’s most densely populated areas in the Central Zone.Despite congestion and saturation of available touristic resources, the number of visitors increases every year, contravening classic touristic demand models that define migration to less congested resources as the outcome of congestion.This analysis will be focused on El Quisco beach, located at Valparaiso’s Region, a touristic destination that clearly represents this process of mass tourism socialization.The goal of this research is to understand the demand composition that social tourism generates, by determining its nature and identifying the factors that define its behavior. These factors are related to the visitor’s origin, displacement, permanence, loyalty, social bonds, gender, income, consumption capacity, and to the degree of satisfaction regarding touristic supplies such as beaches, equipment, and infrastructure.Understanding this demand behavior it is key to develop policies enabling the planning of sustainable social tourism, and allowing for low-income families to access high-quality resources.

Dynamic Redeployment to Counter Congestion or Starvation in Vehicle Sharing Systems

Extensive usage of private vehicles has led to increased traffic congestion, carbon emissions, and usage of non-renewable resources. These concerns have led to the wide adoption of vehicle sharing (ex: bike sharing, car sharing) systems in many cities of the world. In vehicle-sharing systems, base stations (ex: docking stations for bikes) are strategically placed throughout a city and each of the base stations contain a pre-determined number of vehicles at the beginning of each day. Due to the stochastic and individualistic movement of customers,there is typically either congestion (more than required)or starvation (fewer than required) of vehicles at certain base stations. As demonstrated in our experimental results, this happens often and can cause a significant loss in demand. We propose to dynamically redeploy idle vehicles using carriers so as to minimize lost de-mand or alternatively maximize revenue for the vehicle sharing company. To that end, we contribute an optimization formulation to jointly address the redeploy-ment (of vehicles) and routing (of carriers) problemsand provide two approaches that rely on decomposability and abstraction of problem domains to reduce the computation time significantly. Finally, we demonstrate the utility of our approaches on two real world data sets of bike-sharing companies.

A Decision-Aided Situation Awareness Mechanism Based on Multiscale Dynamic Trust

Attacks are always seeking ways of exploiting any existing weakness in wireless network. The purpose of security situation awareness is to recognize, analyze, forecast, and handle the misbehaviors, assisting network management. Nevertheless, the appearance of ubiquitous network and the network convergence technology has made a challenge to realize network security and adaptation. Aiming at these research problems, this paper proposes a decision-aided situation awareness mechanism based on multiscale dynamic trust from the perspective of time and space, which can recognize misbehaviors and regard social network as the research object. We build trust and satisfaction based on Ebbinghaus forgetting regular and spatial correlations. This mechanism carries out decision making assessment through trust authenticity test, logicality test, and feedback parameters. In addition, load balance is used to avoid resource congestion. Simulation analysis demonstrates that compared with other trust mechanisms, this mechanism proposed in this paper can recognize and handle entity attacks more effectively, which is relatively eclectic and realistic in aspect of trust mensuration.

Distinguishing Technical Inefficiency from Desirable and Undesirable Congestion with an Application to Regional Industries in China

Congestion is an important issue that requires the efficiency of decision-making units (DMUs). We first classify conventional congestion into congestion (newly defined) and technical inefficiency, based on prior research and real applications. Modified definitions and mathematical expression of congestion, managerial inefficiency, and technical inefficiency are proposed to better illustrate the differences between them. Several modified models are provided to identify and recognize those types of inefficiencies and congestion. We then extend the model by considering the desirable and undesirable types of congestion simultaneously. The proposed approach is applied and verified by identifying resource congestion and environmental inefficiencies in China’s economic development.

Private Access Fees and Congestion: Is There a Role for Government after All?

We reframe an important debate between Pigou and Knight about the need for government intervention in allocating congestible resources like roads. Knight showed that private toll-setting would achieve an efficient allocation if some motorists commuted to work on an alternative route that was uncongestible. Government intervention was unnecessary. Others have shown that Knight's laissez-faire solution fails if the other road was also congestible but marred their demonstration by excluding private toll-setting on that road as well. We consider a game with simultaneous toll-setting on every congestible road. When we discover that the laissez-faire allocation is inefficient, we consider how the government can improve the private allocation by providing motorists an actual or potential alternative to the privately-priced, congestible resources. Our results apply to a wide range of allocation problems involving congestion: simultaneous tuition setting in private (or charter) schools when students can instead attend a public-school or simultaneous prize-setting in contests to cure diseases when researchers can instead work at NIH.

Simulation of Carpooling Agents with the Janus Platform

Carpooling is an emerging alternative transportation mode that is eco-friendly and sustainable as it enables commuters to save time, travel resource, reduce emission and traffic congestion. The procedure of carpooling consists of a number of steps namely; (i) create a motive to carpool, (ii) communicate this motive with other agents, (iii) negotiate a plan with the interested agents, (iv) execute the agreed plans, and (v) provide a feedback to all concerned agents. The state-of-the-art research work on agent-based modeling is limited to a number of technical and empirical studies that are unable to handle the complex agent behavior in terms of coordination, communication and negotiations. In this paper, we present a conceptual design of an agent-based model (ABM) for the carpooling a that serves as a proof of concept. Our model for the carpooling application is a computational model that is used for simulating the interactions of autonomous agents and to analyze the effects of change in factors related to the infrastructure, behavior and cost. In our carpooling application, we use agent profiles and social networks to initiate our agent communication model and then employ a route matching algorithm, and a utility function to trigger the negotiation process between agents. We plan to, as a part of the future work, develop a prototype of our agent-based carpooling application based on the work presented in this paper. Furthermore, we also intend to carry out a validation study of our results with real data.

Adaptive Congestion Control Protocol (ACCP) for Wireless Sensor Networks

In Wireless Sensor Networks (WSN) when an event is detected there is an increase in data traffic that might lead to packets being transmitted through the network close to the packet handling capacity of the WSN. The WSN experiences a decrease in network performance due to packet loss, long delays, and reduction in throughput. In this paper we developed an adaptive congestion control algorithm that monitors network utilization and adjust traffic levels and/or increases network resources to improve throughput and conserve energy. The traffic congestion control protocol DelStatic is developed by introducing backpressure mechanism into NOAH. We analyzed various routing protocols and established that DSR has a higher resource congestion control capability. The proposed protocol, ACCP uses a sink switching algorithm to trigger DelStatic or DSR feedback to a congested node based on its Node Rank. From the simulation results, ACCP protocol does not only improve throughput but also conserves energy which is critical to sensor application survivability on the field. Our Adaptive Congestion control achieved reliability, high throughput and energy efficiency.

The Research of Power Distribution and Utilization Business Model Based on the Comprehensive Evaluation Model

There are many characters in power distribution and utilization business such as transparent transmission, centralized transmission, various types etc, which cause network delay, severe congestion, and bandwidth resources waste. First, this paper studies and analyzes the needs of power distribution and utilization business, then combined with comprehensive evaluation model, the membership of each power distribution and utilization business is decided, which reflects the reliability and real-time performance of power distribution and utilization business synthetically. According to the value of membership, each business data flow is distinguished by different identifications which change the transparent transmission mode and realize the purpose of network participation.

Pricing Utility-Based Virtual Networks

This paper presents a new pricing mechanism for virtual network (VN) services to regulate the demand for their shared substrate network (SN) resources. The contributions of this article are two-fold; first, we introduce a new time-of-use pricing policy for the SN resources that reflects the effect of resource congestion introduced by VN users. The preferences of the VN users are first represented through corresponding demand-utility functions that quantify the sensitivity of the applications hosted by the VNs to resource consumption, time-of-use and prices during peak-demand periods. We then introduce a novel model of time-varying VNs, where users are allowed to up- or down-scale the requested resources to continuously maximize their utility while minimizing the cost of embedding the VNs onto the SN. The second contribution is a novel hierarchical embedding management approach tailored to efficiently map these dynamic VNs. The proposed VN embedding scheme recasts the VN embedding problem as a subgraph matching one, and introduces a simple heuristics-based matching procedure to find a good VN embedding from a number of candidate solutions obtained in parallel. In contrast to existing solutions, the proposed scheme does not impose any limitations on the size or topology of the VN requests. Instead, the search is customized according to the VN size and the associated utility. Experimental results demonstrate the performance achieved by the proposed work in terms of the increased profit, resource utilization and number of accepted requests.

Operating Protocol and Networking Issues of a Telemedicine Platform Integrating from Wireless Home Sensors to the Hospital Information System

Chronic heart failure (CHF) is among the major causes of hospitalization for elderly citizens. Its considerable impact on patient quality of life, the resources congestion, and the related costs can be efficiently mitigated using remote wireless biosensors networks placed at patient home, able to communicate in secure way over the public Internet with the cardiology departmental Hospital Information System (HIS). In this way, physicians can monitor the situation of several patients at distance and quickly realize and act alterations in vital parameters. In this scenario, the Health@Home (H@H) platform is conceived. The pool of Bluetooth sensors enables patients to daily collect vital signs at home in noninvasive fashion. A home gateway receives and processes all signals before sending them to a server node in charge of interfacing with the usual HIS. The novel concept of operating protocol (OP) represents a list of actions, remotely configurable, that the domestic network has to follow (required measurements, transmissions, comparisons with personalized thresholds, etc.). The first medical tests on 30 patients (1 month) allowed to verify the model, both from the patient and the medical perspective. The main evaluation metrics were usability, flexibility, and reliability of the communication from sensors to HIS.