On the Message Complexity of Global Computations

2010 ◽  
pp. 427-442
Author(s):  
Doron Nussbaum ◽  
Nicola Santoro
Keyword(s):  
Message Complexity

Application of Information Introduced to Dynamic Message Processing and Enjoyment

2018 ◽  
Vol 30 (4) ◽  
pp. 196-206 ◽  
Author(s):  
Byungho Park ◽  
Rachel L. Bailey
Keyword(s):  
Resource Allocation ◽  
Recognition Memory ◽  
Emotional Processing ◽  
Orienting Response ◽  
Structural Features ◽  
Cognitive Resources ◽  
Coding System ◽  
Message Complexity ◽  
Cognitive Resource ◽  
Cognitive Overload

Abstract. In an effort to quantify message complexity in such a way that predictions regarding the moment-to-moment cognitive and emotional processing of viewers would be made, Lang and her colleagues devised the coding system information introduced (or ii). This coding system quantifies the number of structural features that are known to consume cognitive resources and considers it in combination with the number of camera changes (cc) in the video, which supply additional cognitive resources owing to their elicitation of an orienting response. This study further validates ii using psychophysiological responses that index cognitive resource allocation and recognition memory. We also pose two novel hypotheses regarding the confluence of controlled and automatic processing and the effect of cognitive overload on enjoyment of messages. Thirty television advertisements were selected from a pool of 172 (all 20 s in length) based on their ii/cc ratio and ratings for their arousing content. Heart rate change over time showed significant deceleration (indicative of increased cognitive resource allocation) for messages with greater ii/cc ratios. Further, recognition memory worsened as ii/cc increased. It was also found that message complexity increases both automatic and controlled allocations to processing, and that the most complex messages may have created a state of cognitive overload, which was received as enjoyable by the participants in this television context.

AN EFFICIENT DISTRIBUTED ALGORITHM FOR 3-EDGE-CONNECTIVITY

2006 ◽  
Vol 17 (03) ◽  
pp. 677-701 ◽  
Author(s):  
YUNG H. TSIN
Keyword(s):  
Distributed Algorithm ◽  
Computer Network ◽  
Connected Components ◽  
Message Complexity ◽  
Edge Connectivity ◽  
Worst Case ◽  
Dense Networks

A distributed algorithm for finding the cut-edges and the 3-edge-connected components of an asynchronous computer network is presented. For a network with n nodes and m links, the algorithm has worst-case [Formula: see text] time and O(m + nhT) message complexity, where hT < n. The algorithm is message optimal when [Formula: see text] which includes dense networks (i.e. m ∈ Θ(n2)). The previously best known distributed algorithm has a worst-case O(n3) time and message complexity.

Distributed Algorithms for Delay Bounded Minimum Energy Wireless Broadcasting

2010 ◽  
pp. 1677-1697
Author(s):  
Serkan Çiftlikli ◽  
Figen Öztoprak ◽  
Özgür Erçetin ◽  
Kerem Bülbül
Keyword(s):  
Distributed Algorithms ◽  
Spanning Tree ◽  
Minimum Spanning Tree ◽  
Minimum Energy ◽  
Transmission Power ◽  
Message Complexity ◽  
Delay Constraint ◽  
Delay Bound ◽  
Lower Power ◽  
Tree Expansion

In this article, we investigate two different distributed algorithms for constructing a minimum power broadcast tree with a maximum depth ? which corresponds to the maximum tolerable end-to-end delay in the network. Distributed Tree Expansion (DTE) is based on an implementation of a distributed minimum spanning tree algorithm in which the tree grows at each iteration by adding a node that can cover the maximum number of currently uncovered nodes in the network with minimum incremental transmission power and without violating the delay constraint. In Distributed Link Substitution (DLS), given a feasible broadcast tree, the solution is improved by replacing expensive transmissions by transmissions at lower power levels while reserving the feasibility of the tree with respect to the delay bound. Although DTE increases the message complexity to O(n3) from O(n2?) in a network of size n, it provides up to 50% improvement in total expended power compared to DLS.

Broadcasting in Unlabeled Tori

1998 ◽  
Vol 08 (02) ◽  
pp. 177-188 ◽  
Author(s):  
Krzysztof Diks ◽  
Evangelos Kranakis ◽  
Andrzej Pelc
Keyword(s):  
Lower Bound ◽  
A Priori ◽  
Message Complexity ◽  
Arbitrary Size ◽  
Broadcasting Algorithm

We consider broadcasting a message from one node to all other nodes of an asynchronous totally unlabeled torus: neither nodes nor links have a priori assigned labels but they know the topology and the size of the torus. Nodes can send messages of arbitrary size and we are interested in minimizing the total number of messages. A naive broadcasting algorithm in a n × n totally unlabeled torus uses 3n2 + 1 messages, while the obvious lower bound is n2 - 1. The main result of this paper is a broadcasting algorithm using 2n2 + O(n) messages. We also give a lower bound of 1.04n2 - O(n) messages. This is the first result on message complexity of broadcasting in totally unlabeled networks.

Link Assignment for Wireless Sensor Networks with Load Balancing Control

2014 ◽  
Vol 530-531 ◽  
pp. 739-742
Author(s):  
Yan Hong Yang ◽  
Xiao Tong Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Load Balancing ◽  
Dynamic Network ◽  
Wireless Sensor ◽  
Message Complexity ◽  
Original Network ◽  
Performance Results ◽  
Balancing Control ◽  
Made In

This paper proposes and analyzes load balancing control in which numbers of sensors randomly join the original network. Sensors are better suited according to some metrics than arbitrary accessing. Analytic performance results are made in terms of message complexity, link changes and delay. Specially, we discussed the link assignment in dynamic network which is caused adjustment. In load balancing control, sensors are selected based on transmission queue and children number. Results indicate that with observed metrics contributes to better performance.

Bringing order to BGP: Decreasing time and message complexity

2009 ◽  
Vol 53 (12) ◽  
pp. 2241-2256 ◽  
Author(s):  
Anat Bremler-Barr ◽  
Nir Chen ◽  
Jussi Kangasharju ◽  
Osnat Mokryn ◽  
Yuval Shavitt
Keyword(s):  
Message Complexity
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