Science topic

# Distributed Algorithms - Science topic

Distributed Algorithms are a distributed algorithm is an algorithm designed to run on computer hardware constructed from interconnected processors.

Questions related to Distributed Algorithms

Currently, I am exploring federated learning (FL). FL seems going to be in trend soon because of its promising functionality. Please share your valuable opinion regarding the following concerns.

- What are the current trends in FL?
- What are the open challenges in FL?
- What are the open security challenges in FL?
- Which emerging technology can be a suitable candidate to merge with FL?

Thanks for your time.

I was exploring federated learning algorithms and reading this paper (https://arxiv.org/pdf/1602.05629.pdf). In this paper, they have average the weights that are received from clients as attached file. In the marked part, they have considered total client samples and individual client samples. As far I have learned that federated learning has introduced to keep data on the client-side to maintain privacy. Then, how come the server will know this information? I am confused about this concept.

Any clarification?

Thanks in advance.

There is an idea to design a new algorithm for the purpose of improving the results of software operations in the fields of communications, computers, biomedical, machine learning, renewable energy, signal and image processing, and others.

So what are the most important ways to test the performance of smart optimization algorithms in general?

Frameworks such as Apache Storm, Flink, Heron and Spark were developed to run on clusters or cloud. These such kinds of infrastructures do not have memory, CPU and bandwidth limitations. In contrast, computing resources at the network edge are constrained regarding their capabilities. I am aware of the Apache Edgent and Nifi frameworks. However, they were conceived to run locally on a single computing resource. If you want to run them in a distributed infrastructure, you might create your own stack of components (broker + framework).

Please can you tell me what is the motivation of applying multi agent system to the ant colony algorithm since it is a distributed algorithm by nature? does it really improve the solution ?

Hello Every One.

Was trying to implement an algorithm Join Idle Queue in CloudSim. I want to improve the response time in comparison to other policies such as SJF and Minimum execution time. But i realized that in basic package of CloudSim the Submit Cloudlet method of DB class can only be used to allocate cloudlets to Vms on the basis of static approach. to activate my loadbalancer to get an idle Vm i am unable to use this method because all the clodlets are allocated to vms on 0.1 clock time, if i active my loadbalancer here i got an idle Vm but not at 0.1 clock time and unable to allocate the cloudlet to it in this method. somebody told me use powerdatacenter. Guys please help me if anybody knows what to do it will be a great help for me.

Thanks.

I want to know which algorithms do you use in your integrated active chassis control system framework and do you consider the over-actuation due to four electric motors. If so, which torque distribution algorithm is employed in your project?

Sincerely,

Aria Noori Asiabar (M.Sc. degree in vehicle dynamics and control)

I need a simulator to simulate a network of surveillance cameras, to implement my distributed algorithm (I use smart cameras, computer fog and cloud computing)

Please can you tell me what is the motivation of applying multi agent system to swarm algorithms (ie. the ant colony algorithm) since it is a distributed algorithm by nature?

Thank you

In a Research Consultancy, as part of the MBA requirements, analysing data can be complex, particularly of that data is extracted from verbal responses...

Hi Everyone,

Can someone suggest me any summer school (2018), which focus on algorithms. More specifically, distributed algorithms, experimental algorithms and relevant topics.

Your suggestions will be highly appreciated.

Thanks in Advance.

I am trying to develop a distributed algorithm and search for current ones. Your help would be nice

I'm still working to understand estimation of distribution algorithms (EDA) as applied to genetic algorithms. Can the probabilistic models used by EDA for generating new solutions be used by itself? For example, in Bayesian optimization algorithms (BOA) can the Bayesian network that is produced be extracted and used separately as a Bayesian classifier?

What could be an algorithm for computation of Pearson cross-correlation matrix in a distributed environment where my data is divided by id(say: 1-4) and time(say: Jan-Dec) among different nodes. Say node A({id1, Jan}{id2,Jan}), Node B({id3, Jan}, {id4,jan}).

I'm wondering what strategy I could use where I do not have to ship large data from one node to another node as Pearson correlation is a pairwise computation. I'm ok with just transferring small intermediate result between node or How I should partition my data based on id and time so that I efficiently calculate cross-correlation matrix among multiple ids.

It is very time consuming for solving large-scale NP-hard problems. Distributed algorithms based on Map-reduce can speed up the computation and have many successful applications. However, meta-heuristic algorithms such as Tabu search and simulated annealing algorithm are based on single-solution iteration, Hadoop is not good at iteration computation, so few work can be found on distributed iteration meta-heuristic algorithms based on Hadoop or Spark. There is any good implement or idea on iteration meta-heuristics based on Hadoop or Spark? What is its challenge?Thanks.

Several techniques can be applied in Peer-to-Peer networks to handle the presence of malicious nodes (Reputation Systems, Accountability, Distributed Consensus, etc...).

Which one do you think has the best trade off between the capability to discriminate malicious nodes from honest ones, and the cost of the technique (in term of the number of messages for example). Obviously, knowing that none of the previous systems can fully decide (with a 100% accuracy) whether a node is malicious or not .

I want to know which algorithm is regularly used for Approximation algorithm and Distributed algorithm in Dominating set and Wireless Sensor Networks?

implement a Mutual Exclusion Algorithm with simulator software. I don't have a laboratory to test my algorithm

locate the centre node in a wirelss sensor network

distributed algorithm

polynomial complexity

Hello everyone,

I would like to make a simulation of a particular Petri net.

Is there someone that can help me with some ideas or principles on this?

Thank you in advance!

i am working in distribution system side for comparing and analyse my results according to my objective function. i am having some problem with 118 bus system because according to my load flow the base case power loss i am getting is 1291kw but seeing so many papers it is 1296kw. than i have doubt which is correct?

I want to test some parallel implementations of greedy algorithms that solve NP-complete problems such as set-cover or max-matching.

A multi-writer shared storage is the one that allows two writers to modify the same storage object concurrently without imposing any locking. Usually in cases of write collision one of the write operations is visible and the other is hidden, meaning that no read operation will later observe this write. I just wonder if such behavior is useful for any existing applications. For example if it was that the shared storage would implement a file system then would it be OK if one writer would overwrite the changes of a concurrent writer on a single file?

Given an auto-scaling system, we face inputs that have unpredictable patterns and volumes. Because they are allocated per input resource, fluctuations of input volume have much overhead of resource. Do you identify an algorithm that can help to systems performance?

I am working on streams of dataset which yields 256 bit strings. I want to cluster them in real time, (i.e. i don't want to save them in memory, and give each instance a cluster id in real time).

I have a similarity measure for these strings defined by number of 1's in ANDing to the number of 1's in ORing the two strings. (very similar to Jaccard similarity)

I initially worked with sequential leader clustering for this, and it gave great results. The only problem is that, it cannot be applied for distributed systems.

I have found that minhashing and LSH can be implemented for real time text clustering. As per my understandings, Minhashing is used to generate signatures, and then signatures are clustered by banding of the signatures. And, if hash functions are same, the minhash signatures are same in every node in distributed settings.

Can there be a LSH approach for clustering the bitstrings in my case with the defined similarity measure??

Or can i apply minhashing/LSH for minhashing with some trick to get the desired results?

Both require data partitioned. Can distributed algorithms be considered a subtype of parallel algorithm?

When we are connecting different DG's to the particular loads, during non peak hours which DG's are to be selected for the particular load? What kind of algorithm can be used for the selection of DG's in a smartgrid?