Results 1  Obviously you do not have results at the proposal stage  You need to have some idea about what kind of data you will be collected  What statistical procedures will be used?  Then you can answer question or test your hypothesis

Discussion 2  Convince your reader of the potential impact of your proposed research  You need to communicate a sense of enthusiasm and confidence without exaggerating the merits of your research  So you do not need to mention the limitation and weaknesses of the proposed research

Discussion 3  It may be justified by time and financial constrains as well as by the early developmental stage of your research area

Common Mistakes 4  Failure to provide the proper context to frame the research question  Failure to delimit the boundary condition for your research  Failure to cite landmark studies  Failure to accurately present the theoretical and empirical contributions by other researchers

Common Mistakes 5  Failure to stay focused on the research question  Failure to develop a coherent and persuasive argument for the proposed research  Too much detail on minor issues, but not enough detail on major issues

Common Mistakes in Proposal Writing 6  Too much rambling (going all over the map) without a clear sense of direction, the best proposals move forward with ease and grace like a seamless river.  Too many citation lapses and incorrect references  Too long or too short  Slopping writing  Failing to follow the standard style

Research Problems (Internet) 7  Routing algorithms ( BGP)  Communication protocols (TCP)  Algorithms for intelligently selecting a resource in the face of uncertainty  Bandwidth sensing tools  Load balancing algorithms

Research Problems (Internet) 8  Streaming protocols  Structure of the internet  Cost optimization  DNS-related problems  Visualization  Large-scale data processing

Computer Science Fields 9  Algorithms  Artificial Intelligence  Compilers  Computational Complexity  Computer Programming  Computer Graphics  Computer Vision

Computer Science Fields 10  Cryptography  Data Mining  Data Structures  Human-Computer Interaction  Networking  Operating Systems  Programming Languages

Computer Science Fields 11  Robotics  Scientific Computing  Software Engineering  Steganography  Type Theory