This paper explores a unique way in which TheThinking Algorithm adds an extra logical substrate to a web search query using artificial intelligence. Instead of just going after keyword searching, the algorithm tries to assess the motives of the user behind entering a query. The algorithm tries to find the reasons as to why a user has entered a particular query by adding this question with every query: "Sitting in a particular region, why has the person entered such a query?" The Compounded Uniqueness Level applies the concept of geo-location searches. The algorithm allots competency level to the user from the query term using topic trees. The query parsers and indexers in the algorithm are more magnetized into extracting meaningful information from queries and web pages than just indexing the words present in a web page. Clustering the search results help to resolve the ambiguity in a user's query.

Abstract-Maintaining load balancing in a computing cluster is an evident problem in distributed systems and research in this field is not new. The challenges in designing the load balancing algorithms are immense. This paper lists some of those challenges in the design of CPU load balancing algorithm and provides solutions to some of them. The algorithm considers one node in the cluster as the Master Server and another as the Load Balancer. The master server maintains the CPU and IP information of each machine. The nodes in the cluster send their CPU status and IP information to the master server after every 30 seconds. The implementation solves "readers-writers" problem exclusively using sockets. If a number of requests are sent before the next central database update, the load balancer selects other less busy nodes in the cluster. This ensures that all nodes are allocated with the new tasks coming from remote systems, thereby maintaining a load balance among the CPUs. This implementation is highly fault tolerant and reliable, guaranteeing a high probability of task completion. Results show that this scheme handles task allocation in much optimized way and with fewer overheads. The implementation can handle CPUs ranging in numbers from 1 to 255.

Geo-location searching is an important feature for any search engine and research in this field is not new. The only issue that remains is how a search engine know whether a web page belongs to India or the USA? URLs ending with [.in] are the ultimate choice for India but not all web sites from India end with [.in]. This paper describes a technology known as the address parser. The address parser searches for patterns in a web page that communicates address information. The address parser does not parse every web page of a website for extracting the address but only works on those URLs where the probability of finding an address of the website owner is maximum, thereby eliminating false positives. A central knowledge base is built manually, which contains information like States of a country followed by their city names and other relevant information that may help the address parser do precise local indexing. It was observed that the address parser was not only able to recognize the address patterns in the web pages but also indexed them to city specific information. As a result, a person located in Gangtok, Sikkim, India searched for [universities]; the searching module showed the link of [Sikkim Manipal University] first, followed by other links from India. This work also focuses on the importance of the terms contained in the URLs for geographical based indexing and searching.

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