97,107 research outputs found
Revisiting minimum profit conditions in uniform price day-ahead electricity auctions
We examine the problem of clearing day-ahead electricity market auctions
where each bidder, whether a producer or consumer, can specify a minimum profit
or maximum payment condition constraining the acceptance of a set of bid curves
spanning multiple time periods in locations connected through a transmission
network with linear constraints. Such types of conditions are for example
considered in the Spanish and Portuguese day-ahead markets. This helps
describing the recovery of start-up costs of a power plant, or analogously for
a large consumer, utility reduced by a constant term. A new market model is
proposed with a corresponding MILP formulation for uniform locational price
day-ahead auctions, handling bids with a minimum profit or maximum payment
condition in a uniform and computationally-efficient way. An exact
decomposition procedure with sparse strengthened Benders cuts derived from the
MILP formulation is also proposed. The MILP formulation and the decomposition
procedure are similar to computationally-efficient approaches previously
proposed to handle so-called block bids according to European market rules,
though the clearing conditions could appear different at first sight. Both
solving approaches are also valid to deal with both kinds of bids
simultaneously, as block bids with a minimum acceptance ratio, generalizing
fully indivisible block bids, are but a special case of the MP bids introduced
here. We argue in favour of the MP bids by comparing them to previous models
for minimum profit conditions proposed in the academic literature, and to the
model for minimum income conditions used by the Spanish power exchange OMIE
Named data networking for efficient IoT-based disaster management in a smart campus
Disasters are uncertain occasions that can impose a drastic impact on human life and building infrastructures. Information and Communication Technology (ICT) plays a vital role in coping with such situations by enabling and integrating multiple technological resources to develop Disaster Management Systems (DMSs). In this context, a majority of the existing DMSs use networking architectures based upon the Internet Protocol (IP) focusing on location-dependent communications. However, IP-based communications face the limitations of inefficient bandwidth utilization, high processing, data security, and excessive memory intake. To address these issues, Named Data Networking (NDN) has emerged as a promising communication paradigm, which is based on the Information-Centric Networking (ICN) architecture. An NDN is among the self-organizing communication networks that reduces the complexity of networking systems in addition to provide content security. Given this, many NDN-based DMSs have been proposed. The problem with the existing NDN-based DMS is that they use a PULL-based mechanism that ultimately results in higher delay and more energy consumption. In order to cater for time-critical scenarios, emergence-driven network engineering communication and computation models are required. In this paper, a novel DMS is proposed, i.e., Named Data Networking Disaster Management (NDN-DM), where a producer forwards a fire alert message to neighbouring consumers. This makes the nodes converge according to the disaster situation in a more efficient and secure way. Furthermore, we consider a fire scenario in a university campus and mobile nodes in the campus collaborate with each other to manage the fire situation. The proposed framework has been mathematically modeled and formally proved using timed automata-based transition systems and a real-time model checker, respectively. Additionally, the evaluation of the proposed NDM-DM has been performed using NS2. The results prove that the proposed scheme has reduced the end-to-end delay up from 2% to 10% and minimized up to 20% energy consumption, as energy improved from 3% to 20% compared with a state-of-the-art NDN-based DMS
Empowering a helper cluster through data-width aware instruction selection policies
Narrow values that can be represented by less number of bits than the full machine width occur very frequently in programs. On the other hand, clustering mechanisms enable cost- and performance-effective scaling of processor back-end features. Those attributes can be combined synergistically to design special clusters operating on narrow values (a.k.a. helper cluster), potentially providing performance benefits. We complement a 32-bit monolithic processor with a low-complexity 8-bit helper cluster. Then, in our main focus, we propose various ideas to select suitable instructions to execute in the data-width based clusters. We add data-width information as another instruction steering decision metric and introduce new data-width based selection algorithms which also consider dependency, inter-cluster communication and load imbalance. Utilizing those techniques, the performance of a wide range of workloads are substantially increased; helper cluster achieves an average speedup of 11% for a wide range of 412 apps. When focusing on integer applications, the speedup can be as high as 22% on averagePeer ReviewedPostprint (published version
The JStar language philosophy
This paper introduces the JStar parallel programming language, which is a Java-based declarative language aimed at discouraging sequential programming, en-couraging massively parallel programming, and giving the compiler and runtime maximum freedom to try alternative parallelisation strategies. We describe the execution semantics and runtime support of the language, several optimisations and parallelism strategies, with some benchmark results
Single-Producer/Single-Consumer Queues on Shared Cache Multi-Core Systems
Using efficient point-to-point communication channels is critical for
implementing fine grained parallel program on modern shared cache multi-core
architectures.
This report discusses in detail several implementations of wait-free
Single-Producer/Single-Consumer queue (SPSC), and presents a novel and
efficient algorithm for the implementation of an unbounded wait-free SPSC queue
(uSPSC). The correctness proof of the new algorithm, and several performance
measurements based on simple synthetic benchmark and microbenchmark, are also
discussed
Information Centric Networking in the IoT: Experiments with NDN in the Wild
This paper explores the feasibility, advantages, and challenges of an
ICN-based approach in the Internet of Things. We report on the first NDN
experiments in a life-size IoT deployment, spread over tens of rooms on several
floors of a building. Based on the insights gained with these experiments, the
paper analyses the shortcomings of CCN applied to IoT. Several interoperable
CCN enhancements are then proposed and evaluated. We significantly decreased
control traffic (i.e., interest messages) and leverage data path and caching to
match IoT requirements in terms of energy and bandwidth constraints. Our
optimizations increase content availability in case of IoT nodes with
intermittent activity. This paper also provides the first experimental
comparison of CCN with the common IoT standards 6LoWPAN/RPL/UDP.Comment: 10 pages, 10 figures and tables, ACM ICN-2014 conferenc
STATE TRADING VERSUS EXPORT SUBSIDIES: THE CASE OF CANADIAN WHEAT
Canada and the United States have used different trade policies to support their wheat industries. Canada conferred sole export powers to the Canadian Wheat Board, allowing it to price discriminate among markets. The U.S. government has funded transfers to its wheat producers from taxpayers, instead, through export subsidies. This study compares these two ways of supporting producers in terms of their transfer efficiency and overall deadweight losses, the incidence on different domestic interest groups, and their consequences for third party traders. In the analysis we consider the implications of market power of wheat marketing firms for the comparison of policy alternatives in the context of the Canadian wheat industry.International Relations/Trade,
Lightweight Blockchain Framework for Location-aware Peer-to-Peer Energy Trading
Peer-to-Peer (P2P) energy trading can facilitate integration of a large
number of small-scale producers and consumers into energy markets.
Decentralized management of these new market participants is challenging in
terms of market settlement, participant reputation and consideration of grid
constraints. This paper proposes a blockchain-enabled framework for P2P energy
trading among producer and consumer agents in a smart grid. A fully
decentralized market settlement mechanism is designed, which does not rely on a
centralized entity to settle the market and encourages producers and consumers
to negotiate on energy trading with their nearby agents truthfully. To this
end, the electrical distance of agents is considered in the pricing mechanism
to encourage agents to trade with their neighboring agents. In addition, a
reputation factor is considered for each agent, reflecting its past performance
in delivering the committed energy. Before starting the negotiation, agents
select their trading partners based on their preferences over the reputation
and proximity of the trading partners. An Anonymous Proof of Location (A-PoL)
algorithm is proposed that allows agents to prove their location without
revealing their real identity. The practicality of the proposed framework is
illustrated through several case studies, and its security and privacy are
analyzed in detail
- …