DIRECT: A Scalable Approach for Route Guidance in Selfish Orienteering Problems

In this work, we study the combinatorial structure and the computational complexity of Nash equilibria for a certain game that models selfish routing over a network consisting of m parallel links. We assume a collection of n users, each employing a mixed strategy, which is a probability distribution over links, to control the routing of its own assigned traffic. In a Nash equilibrium, each user selfishly routes its traffic on those links that minimize its expected latency cost, given the network congestion caused by the other users. The social cost of a Nash equilibrium is the expectation, over all random choices of the users, of the maximum, over all links, latency through a link.We embark on a systematic study of several algorithmic problems related to the computation of Nash equilibria for the selfish routing game we consider. In a nutshell, these problems relate to deciding the existence of a Nash equilibrium, constructing a Nash equilibrium with given support characteristics, constructing the worst Nash equilibrium (the one with maximum social cost), constructing the best Nash equilibrium (the one with minimum social cost), or computing the social cost of a (given) Nash equilibrium. Our work provides a comprehensive collection of efficient algorithms, hardness results (both as \( \mathcal{N}\mathcal{P} \) -hardness and \( \# \mathcal{P} \) -completeness results), and structural results for these algorithmic problems. Our results span and contrast a wide range of assumptions on the syntax of the Nash equilibria and on the parameters of the system.

One of the most widely used solution concepts for strategic games is the concept of Nash equilibrium. A Nash equilibrium is a state in which no player can improve its objective by unilaterally changing its strategy. A Nash equilibrium is called pure if all players choose a pure strategy, and mixed if players choose probability distributions over strategies. Of special interest are fully mixed Nash equilibria where each player chooses each strategy with non-zero probability. Rosenthal [12] introduced a special class of strategic games, now widely known as congestion games. Here, the strategy set of each player is a subset of the power set of given resources. The players share a private objective function, defined as the sum (over their chosen resources) of functions in the number of players sharing this resource. In his seminal work, Rosenthal showed with help of a potential function that congestion games (in sharp contrast to general strategic games) always admit at least one pure Nash equilibrium. An extension to congestion games are weighted congestion games, in which the players have weights and thus different influence on the congestion of the resources. In (weighted) network congestion games the strategy sets of the players correspond to paths in a network. In order to measure the degradation of social welfare due to the selfish behavior of the players, Koutsoupias and Papadimitriou [8] introduced a global objective function, usually coined as social cost. They defined the price of anarchy, also called coordination ratio, as the worst-case ratio between the value of social cost in a Nash equilibrium and that of some social optimum. Thus the coordination ratio measures the extent to which non-cooperation approximates cooperation. As a starting point for studying the coordination ratio, Koutsoupias and Papadimitriou considered a very simple weighted network congestion game, now known as KP-model. Here, the network consists of a single source and a single destination which are connected by parallel links. The load on a link is the total weight of players assigned to this link. Associated with each link is a capacity representing the rate at which the link processes load. Each of the players selfishly routes from the source to the destination by choosing a probability distribution over the links. The private objective function of a player is defined as its expected latency. In the KP-model the social cost is defined as the expected maximum latency on a link, where the expectation is taken over all random choices of the players. In this paper, we give a thorough survey on the most exciting results on finite (weighted) congestion games and on special classes which are related to the KP-model. In particular, we review the findings on the existence and computational complexity of pure Nash equilibria. Furthermore, we discuss results on the price of anarchy. Last but not least, we survey known facts on fully mixed Nash equilibria.

We study the negative consequences of selfish behavior in a congested network and economic means of influencing such behavior. We consider a model of selfish routing in which the latency experienced by network traffic on an edge of the network is a function of the edge congestion, and network users are assumed to selfishly route traffic on minimum-latency paths. The quality of a routing of traffic is measured by the sum of travel times (the total latency).It is well known that the outcome of selfish routing (a Nash equilibrium) does not minimize the total latency. An ancient strategy for improving the selfish solution is the principle of marginal cost pricing, which asserts that on each edge of the network, each network user on the edge should pay a tax offsetting the congestion effects caused by its presence. By pricing network edges according to this principle, the inefficiency of selfish routing can always be eradicated.This result, while fundamental, assumes a very strong homogeneity property: all network users are assumed to trade off time and money in an identical way. The guarantee also ignores both the algorithmic aspects of edge pricing and the unfortunate possibility that an efficient routing of traffic might only be achieved with exorbitant taxes. Motivated by these shortcomings, we extend this classical work on edge pricing in several different directions and prove the following results.We prove that the edges of a single-commodity network can always be priced so that an optimal routing of traffic arises as a Nash equilibrium, even for very general heterogeneous populations of network users.When there are only finitely many different types of network users and all edge latency functions are convex, we show how to compute such edge prices efficiently.We prove that an easy-to-check mathematical condition on the population of heterogeneous network users is both necessary and sufficient for the existence of edge prices that induce an optimal routing while requiring only moderate taxes.

A Wireless Sensor Network (WSN) normally consists of an exceptionally large number of inexpensive, disposable, robust, small, and low power sensor nodes operational considerately. A Distributed and Scalable Scheduling Access (DSSA) scheme that mitigates in wireless sensor networks handles some mobility with high data loss due to the faults. A virtual grid network in distributed and scalable scheduling access scheme is an effortless method to cluster local sensors but fails in network scalability improvement. Existing, Information Controlled Transmission Power (ICTP) alteration method uses higher transmission powers with additional information than individuals that are less instructive to distribute their object state information with the neighboring nodes. ICTP does not detect faults and outlier sensor nodes in the network and probable safety measures have to be taken against them. To overcome these faulty and energy saving issues, Collaborator Homed Routing (CHR) mechanism is developed in WSN. In CHR, cluster heads aggregate information and relay information to the base station independently for improving system’s transmission power with half amount of energy consuming. Non Cluster Head (NCH) nodes choose a restricted number of objects in the information transmission. Based on the CHR principles, designed and implemented a novel mechanism to handle faulty situations. Using CHR in WSN, cluster head faults are installed to observe the scalability of these mechanisms. Therefore CHR consumes less energy with minimal faults. Experimental results show that proposed routing considerably reduces energy consumption, fault free routing, and reduces the possibility of communication disturbance, network scalability, throughout and link failure ratio is compared to existing method

This paper introduces a new IEEE standard, IEEE 802.15.5,which provides mesh capability for wireless personal area network (WPAN) devices. The standard provides an architectural framework enabling WPAN devices to promote interoperable, stable, and scalable wireless mesh topologies. It is composed of two parts: low-rate WPAN mesh and high-rate WPAN mesh. In this paper, we present only low-rate WPAN mesh because it is designed to support wireless sensor networks. IEEE 802.15.5 low-rate part is a light-weight scalable mesh routing protocol that caters well to the requirements of resource-constrained wireless sensor networks. By binding logical addresses to the network topology, IEEE 802.15.5 obviates the need for route discovery. This eliminates the initial route discovery latency, saves storage space and reduces the communication overhead and energy consumption. A distributed link state scheme is further built atop the block addressing scheme to improve the quality of routes, robustness, and load balancing. The routing scheme scales well with regard to various performance metrics. The standard also provides enhanced functions such as multicast, reliable broadcast, power saving, time synchronization, route tracing and portability. We also present the performance evaluation of major functions performed with a 50-nodes tested deployed over a whole floor (100 × 140 ft2) at CUNY Engineering building. The results testify that the IEEE 802.15.5 will serve well for wireless personal area networks and wireless sensor networks.

Recently, the peer-to-peer (P2P) paradigm has emerged, mainly by file sharing systems such as Napster and Gnutella and in terms of scalable distributed data structures. Due to the decentralization, P2P systems promise an improved robustness and scalability and therefore open also a new view on data integration solutions. However, several design and technical challenges arise in building scalable P2P-based integration systems. We address one of them: the problem of distributed query processing. We discuss strategies of query decomposition and routing based on different kinds of routing indexes and present results of an experimental evaluation.

There are three major trends in the field of Algorithmic Game Theory: computational mechanism design, the price of anarchy, and the computation of equilibria; this talk describes one recent result in each. We show computational complexity lower bounds on truthful and approximately efficient mechanisms; we revisit the Roughgarden-Tardos result on selfish routing when routing decisions are made by the nodes, not the flows; and we show that Nash equilibria can be approximated well in several broad, unexpected, and useful classes of games. (Joint work with Costis Daskalakis, Michael Schapira, Yaron Singer, and Greg Valiant).KeywordsInformation SystemData ProcessingLower BoundComputational ComplexityNash EquilibriumThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Essays on Market Design and Auction Theory Youngwoo Koh This dissertation consists of three essays on market design and auction theory. In the first chapter, we develop a model of decentralized college admissions in which students’ preferences for colleges are uncertain, and colleges must incur costs when their enrollments exceed their capacities. Colleges’ admission decisions then become a tool for strategic yield management, because the enrollment at a college depends on not only students’ uncertain preferences but also other colleges’ admission decisions. We find that colleges’ equilibrium admission decisions exhibit “strategic targeting”—colleges may forgo admitting (even good) students likely sought after by the others and may admit (not as good) students likely overlooked by the others. Randomization in admissions may also emerge. The resulting assignment fails to be efficient (among students, among colleges and among all parties including colleges and students) and leads to justified envy among students. When the colleges consider multiple dimensions of students merits, their evaluations are unlikely to be perfectly correlated. In such a case, colleges may avoid head-on competition by distorting their evaluation to place excessive weight on less correlated dimensions, such as extra curricular activities and nonacademic aspects of students’ application portfolios. Restricting the number of applications or allowing for wait-listing might alleviate colleges’ yield management problem, but the resulting assignments are still inefficient and admit justified envy. Centralized matching via Gale and Shapley’s Deferred Acceptance algorithm eliminates colleges’ yield management problem and justified envy among students and attains efficiency. It also attains the outcome that is jointly optimal among colleges, but some colleges may be worse off relative to decentralized matching. The second chapter studies a keyword auction model where bidders have constrained budgets. In the absence of budget constraints, Edelman, Ostrovsky, and Schwarz (2007) and Varian (2007) analyze “locally envy-free equilibrium” or “symmetric Nash equilibrium” bidding strategies in generalized second-price (GSP) auctions. However, bidders often have to set their daily budgets when they participate in an auction; once a bidder’s payment reaches his budget, he drops out of the auction. This raises an important strategic issue that has been overlooked in the previous literature: Bidders may change their bids to inflict higher prices on their competitors because under GSP, the per-click price paid by a bidder is the next highest bid. We provide budget thresholds under which equilibria analyzed in Edelman, Ostrovsky, and Schwarz (2007) and Varian (2007) are sustained as “equilibria with budget constraints” in our setting. We then consider a simple environment with one position and two bidders and show that a search engine’s revenue with budget constraints may be larger than its revenue without budget constraints. In the third chapter, we study the procurement of an innovation in which firms exert effort and create innovations, where the quality of innovation is stochastic. Both the effort level and the quality of innovation are unverifiable, and the procurer cannot extract up-front payment from the firms. Given the uncertainty of quality realization, there is a tradeoff regarding the number of participating firms in the procurement process: If many firms participate in the process, they may be discouraged from expending their initial investment because each of them has a small chance of winning (we call this incentive effect). At the same time, as the number of participants increases, the procurer has a growing chance of getting a higher quality because of the randomness of the quality realization (sampling effect). Therefore, the procurer faces a nontrivial problem of how many firms to invite in the procurement process. We consider two prominent contest mechanisms, a first-price auction and a fixed-prize tournament. We show that if the randomness is large enough, it is optimal for the buyer to invite as many firms as possible in both mechanisms, and the fixed-prize tournament outperforms the first-price auction. In the limit at which the randomness vanishes, inviting only two firms is optimal in both mechanisms, and the firstprice auction outperforms the fixed-prize tournament. Under the first-price auction, we show that any equilibrium converges to an equilibrium as the randomness diminishes and provide a characterization of the limit equilibrium. We also provide a constructive example of a mixed-strategy equilibrium with two firms when the randomness is moderate.

Over the recent many of years, the use of wireless networks has become very popular. A MANET is a collection of wireless mobile nodes without the use of any fixed network infrastructure or centralized administration networks. Each node in a MANET is free to move independently in any direction and will therefore change its links to other devices frequently. Each must forward traffic unrelated to its own use and therefore be a router. In this paper a performance comparison of three popular mobile ad-hoc network routing protocols i.e. Ad-hoc On-demand Distance Vector Routing (AODV),Interzone Routing Protocol (IERP) and Fisheye State Routing Protocol (FSRP) is presented with variable maximum speed with grid node placement. A network simulator QualNet 6.1 from scalable networks is used to evaluate the performance of these protocols. The performance analysis is based on different network metrics such as Average End to End delay (s), Average Jitter(s), Throughput and Packet delivery ratio.

In this thesis, concepts for developing Spatial Data Infrastructures with an emphasis on visualizing 3D landscape and city models in distributed environments are discussed. Spatial Data Infrastructures are important for public authorities in order to perform tasks on a daily basis, and serve as research topic in geo-informatics. Joint initiatives at national and international level exist for harmonizing procedures and technologies. Interoperability is an important aspect in this context - as enabling technology for sharing, distributing, and connecting geospatial data and services. The Open Geospatial Consortium is the main driver for developing international standards in this sector and includes government agencies, universities and private companies in a consensus process. 
\n3D city models are becoming increasingly popular not only in desktop Virtual Reality applications but also for being used in professional purposes by public authorities. Spatial Data Infrastructures focus so far on the storage and exchange of 3D building and elevation data. For efficient streaming and visualization of spatial 3D data in distributed network environments such as the internet, concepts from the area of real time 3D Computer Graphics must be applied and combined with Geographic Information Systems (GIS). For example, scene graph data structures are commonly used for creating complex and dynamic 3D environments for computer games and Virtual Reality applications, but have not been introduced in GIS so far. 
\nIn this thesis, several aspects of how to create interoperable and service-based environments for 3D spatial data are addressed. These aspects are covered by publications in journals and conference proceedings. The introductory chapter provides a logic succession from geometrical operations for processing raw data, to data integration patterns, to system designs of single components, to service interface descriptions and workflows, and finally to an architecture of a complete distributed service network.
\nDigital Elevation Models are very important in 3D geo-visualization systems. Data structures, methods and processes are described for making them available in service based infrastructures. A specific mesh reduction method is used for generating lower levels of detail from very large point data sets. An integration technique is presented that allows the combination with 2D GIS data such as roads and land use areas. This approach allows using another optimization technique that greatly improves the usability for immersive 3D applications such as pedestrian navigation: flattening road and water surfaces. It is a geometric operation, which uses data structures and algorithms found in numerical simulation software implementing Finite Element Methods. 
\n3D Routing is presented as a typical application scenario for detailed 3D city models. Specific problems such as bridges, overpasses and multilevel networks are addressed and possible solutions described. The integration of routing capabilities in service infrastructures can be accomplished with standards of the Open Geospatial Consortium. An additional service is described for creating 3D networks and for generating 3D routes on the fly. Visualization of indoor routes requires different representation techniques.
\nAs server interface for providing access to all 3D data, the Web 3D Service has been used and further developed. Integrating and handling scene graph data is described in order to create rich virtual environments. Coordinate transformations of scene graphs are described in detail, which is an important aspect for ensuring interoperability between systems using different spatial reference systems. The Web 3D Service plays a central part in nearly all experiments that have been carried out. It does not only provide the means for interactive web-visualizations, but also for performing further analyses, accessing detailed feature information, and for automatic content discovery.
\nOpenStreetMap and other worldwide available datasets are used for developing a complete architecture demonstrating the scalability of 3D Spatial Data Infrastructures. Its suitability for creating 3D city models is analyzed, according to requirements set by international standards. A full virtual globe system has been developed based on OpenStreetMap including data processing, database storage, web streaming and a visualization client.
\nResults are discussed and compared to similar approaches within geo-informatics research, clarifying in which application scenarios and under which requirements the approaches in this thesis can be applied.
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Telecom operators' proliferation, caused by the liberation in the provision of communication services in the European domain, has led in the emergence of demand for small, cost effective core network elements capable of performing both access communication, as well as, traffic routing towards various technology backbones. Bulky equipment is no longer attracting operators' interest, for a number of reasons, summarized in downsize ability (monolithic support of millions of users on a single box is not the case anymore for start up operators), scalability and flexibility to seamlessly integrate advanced services. Especially in the case of UMTS, IP communications are realized over a mixture of heterogeneous transportation technologies often resulting to replication of redundant functions, which limits network performance, complicates its maintenance, reduces scalability and increases operational costs. This paper presents a flexible gateway architecture, which can be accommodated on the access interfaces of UMTS networks to enable realization of generic communication interfaces towards core network databases, supporting user access and traffic routing functions, for improved IP communications performance, enhances UMTS network scalability and reduces maintenance costs. Architectural modularity is achieved by integrating the various database technologies within a common network architecture utilising Storage Area Networks technology.

Through virtualization technologies, modern enterprises can build private clouds to support the daily operations of their subsidiaries and consolidate resources from them. In making these resource allocation and consolidation decisions, they want to maximize the achieved utilities and minimize the incurred costs by their subsidiaries, respectively. However, these subsidiaries very often operate autonomously and have private information about job characteristics and energy costs. Due to this information asymmetry, they might be motivated to behave in their own best interests rather than that of the enterprise. To solve these principal-agent problems, we design a tunable auction under which subsidiaries submit bids and resources are allocated in proportion to their bids. We show that the induced competition game obtains a unique Nash equilibrium, under which hidden characteristics of subsidiaries can be revealed. By using variational inequality techniques, we derive the dynamics of the Nash equilibrium as a function of the auction parameters. We design a feedback control mechanism to dynamically adjust the tunable auction parameters based on observable information such as the bids and the resulting allocations. We prove that our adaptive auction converges to the optimal Nash equilibrium under which the aggregate utility of an enterprise is maximized.

We study distributed load balancing in networks with selfish agents. In the simplest model considered here, there are n identical machines represented by vertices in a network and m > n selfish agents that unilaterally decide to move from one vetex to another if this improves their experienced load. We present several protocols for concurrent migration that satisfy desirable properties such as being based only on local information and computation and the absence of global coordination or cooperation of agents. Our main contribution is to show rapid convergence of the resulting migration process to states that satisfy different stability or balance criteria. In particular, the convergence time to a Nash equilibrium is only logarithmic in m and polynomial in n, where the polynomial depends on the graph structure. Using a slight modification with neutral moves, a perfectly balanced state can be reached after additional time polynomial in n. In addition, we show reduced convergence times to approximate Nash equilibria. Finally, we extend our results to networks of machines with different speeds or to agents that have different weights and show similar results for convergence to approximate and exact Nash equilibria.

Orienteering Problems (OPs) are used to model many routing and trip planning problems. OPs are a variant of the well-known traveling salesman problem where the goal is to compute the highest reward path that includes a subset of vertices and has an overall travel time less than a specified deadline. However, the applicability of OPs is limited due to the assumption of deterministic and static travel times. To that end, Campbell et al. extended OPs to Stochastic OPs (SOPs) to represent uncertain travel times (Campbell et al. 2011). In this article, we make the following key contributions: (1) We extend SOPs to Dynamic SOPs (DSOPs), which allow for time-dependent travel times; (2) we introduce a new objective criterion for SOPs and DSOPs to represent a percentile measure of risk; (3) we provide non-linear optimization formulations along with their linear equivalents for solving the risk-sensitive SOPs and DSOPs; (4) we provide a local search mechanism for solving the risk-sensitive SOPs and DSOPs; and (5) we provide results on existing benchmark problems and a real-world theme park trip planning problem.

Ad hoc wireless networks have emerged as a solution to providing ubiquitous, on-demand connectivity without the need for significant infrastructure deployment. In this thesis we address the privacy problems in two types of emerging wireless ad hoc networks, namely sensor and vehicular networks. Although the content of sensor messages describing “events of interest” may be encrypted to provide confidentiality, the context surrounding these events may also be sensitive and therefore should be protected from eavesdroppers. The source-location privacy problem occurs in sensor networks when adversaries use RF localization techniques to perform hop-by-hop traceback of messages to the source sensor’s location. Our work provides a formal model for this problem and examines the privacy characteristics of different sensor routing protocols. In order to provide efficient and private sensor communications, we devise new techniques to enhance source-location privacy that augment these routing protocols. Similarly, an adversary armed with knowledge of the network deployment, routing algorithms, and the data sink location can infer the temporal patterns and track the spatio-temporal evolution of a sensed event, by monitoring the packet arrivals at the sink. We introduce the temporal privacy problem for delay-tolerant sensor networks, provide an information theoretic formulation and propose adaptive buffering to obfuscate temporal information from the adversary. Sensor networks are also characterized by distinctive traffic patterns, wherein traffic mostly exists when events of interests occur. Due to the direct correlation between the type of event and size of data generated by it, an adversary observing a traffic burst can infer information about the type of event simply from the observed message size. We formulate this traffic privacy problem in terms of information entropy, present a quantifiable means to measure traffic privacy and propose solutions to enhance it. Vehicular ad hoc networks represent a promising new communication paradigm that can facilitate many new forms of automotive applications. We present a robust and efficient security and privacy framework, for such networks, that uses identity-based cryptography. We show that our framework provides authentication, confidentiality, non-repudiation and message-integrity. Further, it supports scalable, user-customizable privacy through short-lived, unforgeable, pseudonyms.