This paper describes a general quantum lower bounding technique for the communication complexity of a function that depends on the inputs given to two parties connected via paths, which may be shared with other parties, on a network of any topology. The technique can also be employed to obtain a lower-bound of the quantum communication complexity of some functions that depend on the inputs distributed over all parties on the network. As a typical application, we apply our technique to the distinctness problem of deciding whether there are a pair of parties with identical inputs, on a k-party ring; almost matching upper bounds are also given.

Network caches reduce network traffic as well as user response time. When implementing network caches, the object replacement problem is one of the core problems; The problem is to determine which objects should be evicted from a cache when there is insufficient space. This paper first formalizes the problem and gives a simple but sufficient condition for deterministic online algorithms to be competitive. Based on the condition, a general framework to make a non-competitive algorithm competitive is constructed. As an application of the framework, an online algorithm, called Competitive_SIZE, is proposed. Both event-driven and trace-driven simulations show that Competitive_SIZE is better than previously proposed algorithms such as LRU (Least Recently Used).

This paper describes the concept of an adaptive network, that is, a network environment that can rapidly and autonomously adapt its behavior according to network conditions and traffic status. The user interface of the adaptive network can access any resource in the network as a memory-mapped I/O device, as if it were attached to the local bus of the user's PC. This network concept has several benefits. From the application development viewpoint, no network related programming is required, and applications do not have to be modified even if the network topologies and protocols are changed. Network maintenance and upgrading can be done anytime without having to worry about the application users, because the network itself is concealed from the applications. In addition, the reconfigurable hardware technology functions as an autonomous network control through the use of a lower-layer protocol. We developed a testbed that makes heterogeneous resources available to users and used it to demonstrate the feasibility of our concept by implementing and running some applications over it.

An ordered binary decision diagram (OBDD) is a directed acyclic graph for representing a Boolean function. OBDDs are widely used in various areas which require Boolean function manipulation, since they can represent efficiently many practical Boolean functions and have other desirable properties. However, there is very little theoretical research on the complexity of constructing an OBDD. In this paper, we prove that the optimal variable ordering problem of a shared BDD is NP-complete, and briefly discuss the approximation hardness of this problem and related OBDD problems.

Caching web files reduces user response time as well as network traffic. When implementing caches, the file caching problem must be addressed; the problem is how to determine which files should be evicted from a cache when there is insufficient space for storing a new file so that the sum of the mis-hit (fault) file costs is minimized. Greedy-Dual-Size (GDS) is the best online algorithm in terms of competitiveness, i. e. , (k)/(k-h+1)-competitive, where k and h are the storage space of, respectively, GDS and an optimal offline algorithm. GDS performs very well even in trace-driven simulations. The worst-case time taken to service a request is another important measure for online file caching algorithms since slow response times render caching meaningless from the client's view point. This paper proposes a fast randomized (k)/(k-h+1)-competitive algorithm that performs in O(2log ^* k) time per file eviction or insertion, whereas GDS takes O(log k) time, where 2log ^* k is a much slower increasing function than log k. To confirm its practicality, we conduct trace driven simulations. Experimental results show that our algorithm attains only slightly worse byte hit rates and sufficiently large reduced latency in comparison with GDS, and our algorithm is a good candidate for caches requiring high-speed processing such as second-level caches in the large networks.