Distributed apps and the browser

Wondering what the possibilities of exploiting the browser are to execute distributed applications, hopefully extending around http://des.codeplex.com Would be cool if browser users could voluntarily share their machines computing power for distributed application needs.

Why browser ? Simply because that is the most used app in an internet connected environment.

 Possibilities :

 1.) Javascript based apps - exploiting the underlying machine structures for threading, figuring out idle time might not be really feasible though AJAX could provide some capabilities.

 2.) HTML5 - a bit more promising, but how do you make sure the application lives outside the browsing session/page as you would want the processing to continue even after user moves across pages. This is worth a read : http://dev.w3.org/html5/workers/

 3.) Browser plugins/extensions/apps - worth a detailed research. As these components live within the browser app and not necessarily within a browsing page session. With enough security rights set-up, these components could in fact access the entire computing power of the underlying machine. Interesting.

Anyone currently implementing open source solutions around these areas / having thoughts , do ping me please.

ConsistentHash implementation in C# 4.0

For those not familiar with ConsistentHash, start here: Consistent Hashing

The following is an attempt to implement the functionality using features of C# 3/4. I needed this functionality for the distributed cache project that I was working on (Available at HoC )

namespace HoC.Common
{
    public class ConsistentHash  : ICloneable
    {
        SortedList<string, string> itemCircle = new SortedList<string, string>();

        public string GetNearestItem(string key)
        {
            if (itemCircle.Count == 0)
                throw new ConsistentHashCircleEmpty();

            string keyHash = Hasher.GetHash(key);

            //find the last item that is just after the passed in key (clockwise)
            Func<KeyValuePair<string, string>, bool> stringCompare = x => (x.Key.CompareTo(keyHash) > 0);
            KeyValuePair<string, string> item = itemCircle.FirstOrDefault(stringCompare);

            if (string.IsNullOrEmpty(item.Key)) 
            {
                //if no item, fallback to the first item => traverse circle clockwise 
                return itemCircle.First().Value; 
            }

            return item.Value;
        }

        public void StoreItem(string item)
        {
            string hash = Hasher.GetHash(item);
            itemCircle[hash] = item;
        }

        public void RemoveItem(string item)
        {
            string hash = Hasher.GetHash(item);
            if (itemCircle.ContainsKey(hash))
                itemCircle.Remove(hash);
        }

        public string GetNextItemInCircle(string key)
        {
            return GetNearestItem(key);
        }

        //this function traverses anticlockwise, whereas GetNearestItem() traverses clockwise
        public string GetPreviousItemInCircle(string key)
        {
            if (itemCircle.Count == 0)
                throw new ConsistentHashCircleEmpty();

            string keyHash = Hasher.GetHash(key);

            //traverse, anticlock wise , find first item
            Func<KeyValuePair<string, string>, bool> stringCompare = x => (x.Key.CompareTo(keyHash) < 0);
            KeyValuePair<string, string> item = itemCircle.FirstOrDefault(stringCompare);

            if (string.IsNullOrEmpty(item.Key))
            {
                //if no item, fallback to the last item => traverse circle anti clockwise 
                return itemCircle.Last().Value;
            }

            return item.Value;
        }



        public object Clone()
        {
            return (ConsistentHash)MemberwiseClone();
        }
    }

    class ConsistentHashCircleEmpty : ApplicationException
    {

    }


}

Couple of drill downs:

1.) Basically each objects gets assigned a hash (Hasher class internally uses RIPEMD160Managed) so that it can be arranged in the circle and then gets stored to the internal circle. RIPEMD160Managed though a bit slower, supposedly has the lowest collision.

2.) The circle as seen is implemented using a SortedList list class - itemCircle

3.) The core functionality is implemented using the two methods:

3.1) GetNearestItem : This method traverses clockwise - basically find the object that comes up next in the sorted list after the given key.

3.2) GetPreviousItemInCircle : Opposite of GetNearestItem. Traverses anti-clockwise.

In the project that I use this internally, the objects are all serializable, hence the objects could be easily represented as a string.

Object Pool - Quick and Short in .NET 4.0

A simple object pool that could be used to maintain a set of objects readily available in memory, especially if you see that the object creation time is heavy. Eg:- creation of a MemoryStream on a need basis is typically time consuming in a server based app. In this case, it could best to have a set of MemoryStream objects readily available in memory. But, we definitely have to make sure to couple of things first :

1.) The way the object pool is filled happens is async.
2.) Access to a pool instance from the client app is thread safe.

To solve 1, we could exploit the AsyncMethodCaller together with its BeginInvoke(), while to make sure that the access to the pool is thread safe, we could check out the ConcurrentBag in .NET 4.0. So, where is the code?!

namespace HoC.Client
{
    /// <summary>
    /// maintains a pool/list of objects, provides it on request
    /// usually used for classes whose construction call is heavy
    /// </summary>
    /// <typeparam name="W"></typeparam>
    public class ObjectInstancePool<W>
    {
        private const int objectCount = 20; //can be updated to receive through the constructor
        private ConcurrentBag<W> objectList = new ConcurrentBag<W>();

        public ObjectInstancePool()
        {
            //refresh the bag first
            new AsyncMethodCaller(Filler).BeginInvoke(null, null);
        }

        public W GetInstance()
        {
            W result;

            if (!(objectList.TryTake(out result)))
            {
                result = Activator.CreateInstance<W>();
            }
            else
                new AsyncMethodCaller(Filler).BeginInvoke(null, null); //refresh the bag
            
            return result;
        }

        public delegate void AsyncMethodCaller();

        private void Filler()
        {
            while (objectList.Count < objectCount)
            {
                objectList.Add(Activator.CreateInstance<W>());
            }
        }
    }
}

I totally like it short and sweet :)

Tree-Of-Trust

Overview

Enterprise applications of today are no longer independent, but dependent on other applications, services and components for completing their functionality. Authenticating/Trusting another application typically requires having a new authentication/identity management module written for each new application that is integrated. With the advent of claims based/token based authentication, this pain has been eased very much for a developer. Supporting protocols, standards and frameworks such as SAML, WS-Security, WS-Federation, WIF, ADFS etc playing a huge role.

As of today, A developer for application A requiring access to use services of application B would configure the identity providers supported by B to trust A. As this task is most of the time manual and done as part of the deployment phase, the identity management today can be treated static as such. In a world where SOA is exploited, there comes a need to build trusts dynamically, in the same manner as a service is discovered dynamically.

Influences:
Similar to humans who build trust based on relationships, introductions, recommendations etc, what is proposed in the "dynamic tree of trust" topic area is to have a mechanism that includes new frameworks, protocols, markups, standards that collectively assist in building trust dynamically.

Possibility 1:
An application A wanting to access the functionality/services of an application B can claim that its trusted by another set of applications and provide this set of trust using a markup language to application B. Application B can go through its list of internal tree of trusts and figure out if the trust claims are authentic.

Possibility 2:
An application A wanting to access the functionality/services of an application B can send its identity to application B. Application B internally can apply its 'tree-of-trust' locator algorithm to check if there is any identity provider that appears to know this application A.

Ranking trust:
A ranking mechanism can be used by application B to get the effective-trust index using :
a.) Number of providers that support/trust application A
b.) Depth/level within the 'tree-of-trust'.

Research Possibilities:
1.) Research into dynamically building trust; devise a fool-proof mechanism.
2.) Research into developing a set of
(1.1) protocols
(1.2) standards
(1.3) markups and a
(1.4) sample framework for applications to more easily build trust dynamically without any human interventions, while considering any current trends in claims based authentication/WS-* standards. Especially WS-Federation, WS-Trust.
3.) Research into machine learning mechanisms can be included within the framework to have more robust trust learning mechanism such that the effective ranking is based on prior identity success/failures.
4.) Research into more effective traversal algorithms when the logical structure (not necessarily implementation) of the trust-tree is tree based.
4.1) Research into querying identity providers n level deep on the authenticity of the requestor.
5.) Research into applications in mobile devices.


Applicable thoughts:
1.) Hard Trust - A direct trust setup on an identity provider
2.) Soft Trust - A trust that was build up dynamically. ST (0.5), ST(0.8) etc, wherein the index indicates the effective trust index/rank
3.) On-Behalf-Of – A trust that is directly vouched by another.