Answer:
A small company is requesting a quote to refresh its wireless network. The company currently runs 60 autonomous APs and has plans to increase wireless density by 50% in the near future. The requirements state that the chosen solution should significantly decrease the management overhead of the current wireless network. The following should be recommended by the vendor in response to the quote request:
B. The use of autonomous APs with a wireless controller.
Explanation:
- The option A and D are not correct as the use of lightweight APs are not required here because they are already using autonomous APs which are fulfilling their needs.
- The option B is correct as the use of autonomous APs with a wireless controller will allow them to decrease the management overhead as the wireless controller is used to manage the Access points in larger quantities.
- The option C is incorrect as the load balancers are used to increase the capacity and reliability of applications as they distribute the traffic over number of servers so it is unable to decrease the management overhead.
Answer:
Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem.
If a Greedy Algorithm can solve a problem, then it generally becomes the best method to solve that problem as the Greedy algorithms are in general more efficient than other techniques like Dynamic Programming. But Greedy algorithms cannot always be applied. For example, the Fractional Knapsack problem (See this) can be solved using Greedy, but 0-1 Knapsack cannot be solved using Greedy.
The following are some standard algorithms that are Greedy algorithms.
1) Kruskal’s Minimum Spanning Tree (MST): In Kruskal’s algorithm, we create an MST by picking edges one by one. The Greedy Choice is to pick the smallest weight edge that doesn’t cause a cycle in the MST constructed so far.
2) Prim’s Minimum Spanning Tree: In Prim’s algorithm also, we create an MST by picking edges one by one. We maintain two sets: a set of the vertices already included in MST and the set of the vertices not yet included. The Greedy Choice is to pick the smallest weight edge that connects the two sets.
3) Dijkstra’s Shortest Path: Dijkstra’s algorithm is very similar to Prim’s algorithm. The shortest-path tree is built up, edge by edge. We maintain two sets: a set of the vertices already included in the tree and the set of the vertices not yet included. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from source to the set that contains not yet included vertices.
4) Huffman Coding: Huffman Coding is a loss-less compression technique. It assigns variable-length bit codes to different characters. The Greedy Choice is to assign the least bit length code to the most frequent character. The greedy algorithms are sometimes also used to get an approximation for Hard optimization problems. For example, the Traveling Salesman Problem is an NP-Hard problem. A Greedy choice for this problem is to pick the nearest unvisited city from the current city at every step. These solutions don’t always produce the best optimal solution but can be used to get an approximately optimal solution.
The characteristics and definitions for each concept are stated below:
Rift zone
- Definition: a characteristic of shield-type volcanoes where linear cracks appear in near their premises
- Characteristic: near the continental margin
Abyssal plain
- Definition: a flat area found under the ocean, found in depths ranging from 3,000 metres and 6,000 metres
- Characteristic: very flat part of ocean floor
Ocean trench
- Definition: a very long ditch in the ocean floor
- Characteristic: site of seafloor spreading
Seamount
- Definition: a mountain located on the ocean floor
- Characteristic: underwater volcano