Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe Energy Complexity of Broadcast
64
0
0.0
(
0
)
Added by
Yi-Jun Chang
Publication date
2017
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Energy is often the most constrained resource in networks of battery-powered devices, and as devices become smaller, they spend a larger fraction of their energy on communication (transceiver usage) not computation. As an imperfect proxy for true energy usage, we define energy complexity to be the number of time slots a device transmits/listens; idle time and computation are free. In this paper we investigate the energy complexity of fundamental communication primitives such as broadcast in multi-hop radio networks. We consider models with collision detection (CD) and without (No-CD), as well as both randomized and deterministic algorithms. Some take-away messages from this work include: 1. The energy complexity of broadcast in a multi-hop network is intimately connected to the time complexity of leader election in a single-hop (clique) network. Many existing lower bounds on time complexity immediately transfer to energy complexity. For example, in the CD and No-CD models, we need $Omega(log n)$ and $Omega(log^2 n)$ energy, respectively. 2. The energy lower bounds above can almost be achieved, given sufficient ($Omega(n)$) time. In the CD and No-CD models we can solve broadcast using $O(frac{log nloglog n}{logloglog n})$ energy and $O(log^3 n)$ energy, respectively. 3. The complexity measures of Energy and Time are in conflict, and it is an open problem whether both can be minimized simultaneously. We give a tradeoff showing it is possible to be nearly optimal in both measures simultaneously. For any constant $epsilon>0$, broadcast can be solved in $O(D^{1+epsilon}log^{O(1/epsilon)} n)$ time with $O(log^{O(1/epsilon)} n)$ energy, where $D$ is the diameter of the network.
rate research
Read More
We present simple deterministic algorithms for subgraph finding and enumeration in the broadcast CONGEST model of distributed computation: -- For any constant $k$, detecting $k$-paths and trees on $k$ nodes can be done in $O(1)$ rounds. -- For any constant $k$, detecting $k$-cycles and pseudotrees on $k$ nodes can be done in $O(n)$ rounds. -- On $d$-degenerate graphs, cliques and $4$-cycles can be enumerated in $O(d + log n)$ rounds, and $5$-cycles in $O(d^2 + log n)$ rounds. In many cases, these bounds are tight up to logarithmic factors. Moreover, we show that the algorithms for $d$-degenerate graphs can be improved to optimal complexity $O(d/log n)$ and $O(d^2/log n)$, respectively, in the supported CONGEST model, which can be seen as an intermediate model between CONGEST and the congested clique.
In this paper, we consider the Byzantine reliable broadcast problem on authenticated and partially connected networks. The state-of-the-art method to solve this problem consists in combining two algorithms from the literature. Handling asynchrony and faulty senders is typically done thanks to Gabriel Brachas authenticated double-echo broadcast protocol, which assumes an asynchronous fully connected network. Danny Dolevs algorithm can then be used to provide reliable communications between processes in the global fault model, where up to f processes among N can be faulty in a communication network that is at least 2f+1-connected. Following recent works that showed that Dolevs protocol can be made more practical thanks to several optimizations, we show that the state-of-the-art methods to solve our problem can be optimized thanks to layer-specific and cross-layer optimizations. Our simulations with the Omnet++ network simulator show that these optimizations can be efficiently combined to decrease the total amount of information transmitted or the protocols latency (e.g., respectively, -25% and -50% with a 16B payload, N=31 and f=4) compared to the state-of-the-art combination of Brachas and Dolevs protocols.
In virtualized data centers, consolidation of Virtual Machines (VMs) on minimizing the number of total physical machines (PMs) has been recognized as a very efficient approach. This paper considers the energy-efficient consolidation of VMs in a Cloud Data center. Concentrating on CPU-intensive applications, the objective is to schedule all requests non-preemptively, subjecting to constraints of PM capacities and running time interval spans, such that the total energy consumption of all PMs is minimized (called MinTE for abbreviation). The MinTE problem is NP-complete in general. We propose a self-adaptive approached called SAVE. The approach makes decisions of the assignment and migration of VMs by probabilistic processes and is based exclusively on local information, therefore it is very simple to implement. Both simulation and real environment test show that our proposed method SAVE can reduce energy consumption about 30% against VMWare DRS and 10-20% against EcoCloud on average.
The problem of attaining energy efficiency in distributed systems is of importance, but a general, non-domain-specific theory of energy-minimal scheduling is far from developed. In this paper, we classify the problems of energy-minimal scheduling and present theoretical foundations of the same. We derive results concerning energy-minimal scheduling of independent jobs in a distributed system with functionally similar machines with different working and idle power ratings. The machines considered in our system can have identical as well as different speeds. If the jobs can be divided into arbitrary parts, we show that the minimum-energy schedule can be generated in linear time and give exact scheduling algorithms. For the cases where jobs are non-divisible, we prove that the scheduling problems are NP-hard and also give approximation algorithms for the same along with their bounds.
The Reliable Broadcast concept allows an honest party to send a message to all other parties and to make sure that all honest parties receive this message. In addition, it allows an honest party that received a message to know that all other honest parties would also receive the same message. This technique is important to ensure distributed consistency when facing failures. In the current paper, we study the ability to use RR to consistently transmit a sequence of input values in an asynchronous environment with a designated sender. The task can be easily achieved using counters, but cannot be achieved with a bounded memory facing failures. We weaken the problem and ask whether the receivers can at least share a common suffix. We prove that in a standard (lossless) asynchronous system no bounded memory protocol can guarantee a common suffix at all receivers for every input sequence if a single party might crash. We further study the problem facing transient faults and prove that when limiting the problem to transmitting a stream of a single value being sent repeatedly we show a bounded memory self-stabilizing protocol that can ensure a common suffix even in the presence of transient faults and an arbitrary number of crash faults. We further prove that this last problem is not solvable in the presence of a single Byzantine fault. Thus, this problem {bf separates} Byzantine behavior from crash faults in an asynchronous environment.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
