In this work, we investigate the problem of joint optimization over placement and routing network function chains in data centers. offline case, demonstrate that a classical randomization algorithm works well derive new bound on performance sub-optimality gap. online prove fundamental lower resource violation propose combines techniques from multiplicative weight update primal-dual paradigms. This asymptotically achieves best possible terms allocation among all algorithms. We applicability...

Network functions typically need to be visited in a specific order meet certain objectives, giving rise the notion of Service Function Chaining. Software-Defined-Networking enables fine-grained traffic routing optimization while satisfying correct traversal network functions. In this work, we investigate problem maximizing throughput SDN-enabled networks with respect service chaining specifications under both traditional and new constraints. Besides algorithm design, also derive rigorous...

Traditionally, offline optimization of power systems is acceptable due to the largely predictable loads and reliable generation. The increasing penetration fluctuating renewable generation internet-of-things devices allowing for fine-grained controllability have led diminishing applicability in domain, redirected attention online methods. However, a broad topic that can be applied motivated by different settings, operated on time scales, built theoretical foundations. This paper reviews...

We propose a novel framework of using parsimonious statistical model, known as mixture Gaussian trees, for modeling the possibly multimodal minority class to solve problem imbalanced time-series classification. By exploiting fact that close-by time points are highly correlated due smoothness time-series, our model significantly reduces number covariance parameters be estimated from O(d(2)) O(Ld), where L is components and d dimensionality. Thus, particularly effective high-dimensional with...

This paper addresses the distributed optimal frequency control of power systems considering a network-preserving model with nonlinear flows and excitation voltage dynamics. Salient features proposed strategy are fourfold, first, nonlinearity is considered to cope large disturbances, second, only part generators controllable, third, no load measurement required, fourth, communication connectivity required for controllable generators. To this end, benefiting from concept "virtual demand," we...

This paper investigates the online station assignment for (commercial) electric vehicles (EVs) that request battery swapping from a central operator, i.e., in absence of future information service has to be assigned instantly each EV upon its request. Based on EVs' locations, availability fully-charged batteries at stations system, as well traffic conditions, aims minimize cost EVs and congestion stations. Inspired by polynomial-time offline solution via bipartite matching approach, we...

This paper investigates a data-driven countermeasure for price spoofing in the context of cyber security and market-based frequency regulation. Market-based control transmission power networks relies on cyber-physical infrastructure, which raises questions system vulnerability relation to cyber-security. In this paper, we consider challenge engineering robust controller presence spoofing, i.e. where hacking mechanisms adjust signals an ex-post market. We extend recently developed algorithm...

This paper studies online optimization under inventory (budget) constraints. While is a well-studied topic, versions with constraints have proven difficult. We consider formulation of inventory-constrained that generalization the classic one-way trading problem and has wide range applications. present new algorithmic framework, CR-Pursuit, prove it achieves optimal competitive ratio among all deterministic algorithms (up to problem-dependent constant factor) for optimization. Our algorithm...

This paper studies how the efficiency of an online platform is impacted by degree to which access participants open or controlled. The study motivated emerging trend within platforms impose increasingly fine-grained control over options available participants. While early allowed access, e.g., Ebay allows any seller interact with buyer; modern often matches directly, Uber directly drivers riders. performed goal achieving more efficient market outcomes. However, results in this highlight that...

We compare the efficiencies and robustness of four transport networks that can be possibly formed as a result deliberate city planning. The are constructed based on their spatial resemblance to cities Manhattan (lattice), Sudan (random), Beijing (single-blob) Greater Cairo (dual-blob). For given type, genetic algorithm is employed obtain an optimized set bus routes. then simulate how commuter travels using Yen's algorithms for k shortest paths adjacency matrix. cost traveling such walking...

This paper studies network design and efficiency loss in open discriminatory access platforms under networked Cournot competition. In platforms, every firm connects to market, while limit connections between firms markets improve social welfare. We provide tight bounds on the of both platforms; (i) that at a Nash equilibrium is bounded by 3/2, (ii) for we greedy algorithm optimizing guarantees 4/3, an assumption linearity cost functions.

This paper studies network design and efficiency loss in online platforms using the model of networked Cournot competition. We consider two styles platforms: open access discriminatory platforms. In platforms, every firm can connect to market, while limit connections between firms markets order improve social welfare. Our results provide tight bounds on both For we show that at a Nash equilibrium is upper bounded by 3/2. case prove that, under an assumption linearity cost functions, greedy...

This paper formulates an optimal station assignment problem for electric vehicle (EV) battery swapping that takes into account both temporal and spatial couplings. The goal is to reduce the total EV cost congestion due temporary shortage in supply of available batteries. We show reducible minimum weight perfect bipartite matching problem. leads efficient solution based on Hungarian algorithm. Numerical results suggest proposed provides a significant improvement over greedy heuristic assigns...

This paper formulates a multi-period optimal station assignment problem for electric vehicle (EV) battery swapping that takes into account both temporal and spatial couplings. The goal is to reduce the total EV cost congestion due temporary shortage in supply of available batteries. We show reducible minimum weight perfect bipartite matching problem. leads an efficient solution based on Hungarian algorithm. Numerical results suggest proposed provides significant improvement over greedy...

We propose a novel framework of using parsimonious statistical model, known as mixture Gaussian trees, for modelling the possibly multi-modal minority class to solve problem imbalanced time-series binary classification. By exploiting fact that close-by time points are highly correlated, our model significantly reduces number covariance parameters be estimated from O(d <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) O(Ld), L denotes...

Increasing renewable energy increases uncertainty in systems. As a consequence, generator-side control for frequency regulation, impacted by the slow reaction of generators to meet urgent needs, may no longer suffice. With increasing integration smart appliances which are able sense, communicate and control, load-side can help alleviate aforementioned problem as it reacts fast helps localize disturbances. However, almost all existing methods optimal require full information coverage system....

Platforms: How Much and What Should They Control? Platforms exert control in many ways: from determining which buyers are shown to sellers directly controlling allocation of aggregate supply across different consumer markets. should platforms exercise increase social welfare? In “Transparency Control for Networked Markets,” authors J. Pang, W. Lin, H. Fu, Kleeman, E. Bitar, A. Wierman examine the trade-offs that emerge between efficiency loss, transparency, platform designs. show open access...

We propose a framework for constructing microscopic traffic models from acceleration patterns that can in principle be experimental measured and proper averaged. The exact model thus obtained used to justify the consistency of various popular literature. Assuming analyticity model, we suggest controlled expansion around constant velocity, uniform headway "ground state" is way different effective models. unique ground state any fixed average density, discuss universal properties resulting...

Using the optimal velocity (OV) model as an example, we show that in non-linear regime there is emergent quantity gives extremum headways cluster formation, well coexistence curve separating absolute stable phase from metastable phase. This independent of density traffic lane, and determines intrinsic scale characterizes dynamics localized quasisoliton structures given by time derivative headways. The analogous to "charge" quasisolitons controls strength interaction between multiple...

In networked markets, information can help firms make better decisions on which market (platform), and how much, to participate. However, these markets may be temporally separated, e.g., independent system operators in different geographical locations. We model via Cournot but instead consider the participation of one firm either with realization (or full information) a random market, or only statistics modeled by an additive zero-mean variable maximal price. show that not knowing would...

With the rapid growth of electric vehicles (EVs), EV aggregators have been playing a increasingly vital role in power systems by not merely providing charging management but also participating wholesale electricity markets. This work studies optimal real-time bidding strategy for an aggregator. Since process EVs is time-coupled, it necessary to consider future operational conditions (e.g., arrivals) when deciding current strategy. However, accurately forecasting challenging under inherent...